Platform Architect - Search & Retrieval Systems Job at AlphaSense (Bengaluru)

Staff AI Context Engineer

MagicSchool is seeking a Staff AI Context Engineer to architect and enhance the ...

Location

United States

Salary:

205000.00 - 240000.00 USD / Year

EdTech Jobs

Expiration Date

Until further notice

Requirements

Deep Knowledge Systems Experience: 5+ years building large-scale information systems with at least 2+ years in staff/senior roles. Extensive hands-on experience with RAG systems, knowledge graphs, or semantic search platforms in production environments.
Graph Database Expertise: Deep experience with graph databases (Neo4j, Neptune, or similar), including schema design, query optimization (Cypher, Gremlin), and building graph-based applications.
RAG & Retrieval Mastery: Demonstrated expertise building production RAG systems including embedding selection, chunking strategies, hybrid search, reranking, and retrieval evaluation. Familiarity with vector databases (pgvector, Pinecone, Weaviate, Qdrant).
Embedding & NLP Background: Strong understanding of embedding models (sentence transformers, domain-specific embeddings), fine-tuning approaches, and semantic similarity. Experience with document processing, entity extraction, and text chunking for optimal retrieval.
Technical Stack: Strong coding skills in Python and/or TypeScript/Node.js. Experience with our stack (TypeScript, Node.js, PostgreSQL, NextJS, Supabase) plus graph databases and vector stores. Familiarity with LLM APIs and context management patterns.
Information Architecture: Deep understanding of information retrieval theory, semantic search, knowledge representation, and strategies for organizing complex domain knowledge for both human and AI consumption.
Leadership & Impact: Track record of architecting complex knowledge systems, making high-leverage technical decisions about information architecture, and mentoring engineers on sophisticated retrieval and graph concepts.

Job Responsibility

Knowledge Graph & Semantic Architecture: Architect and implement graph-based knowledge systems (Neo4j, Neptune, etc) that represent educational content relationships, standards alignments, prerequisite chains, curriculum coherence, learning progressions, and pedagogical connections.
Graph Schema & Ontology Development: Design and evolve ontologies and schemas for educational content, defining entity types (standards, concepts, skills, assessments), relationship semantics, and property models.
GraphRAG Implementation: Build GraphRAG systems that combine knowledge graph traversal with vector similarity, enabling agents to retrieve contextually connected educational materials.
Retrieval Pipeline Architecture: Architect and implement sophisticated retrieval-augmented generation pipelines including hybrid search (dense + sparse), multi-stage retrieval, reranking strategies, and query understanding.
Embedding & Vectorization Strategy: Design and operationalize embedding pipelines for educational content, selecting and fine-tuning embedding models, implementing chunking strategies, and managing vector stores at scale.
Retrieval Evaluation & Optimization: Design evaluation pipelines that measure retrieval precision, recall, MRR, and NDCG across educational content types. Continuously optimize retrieval quality.
Document Ingestion & Processing: Build robust ingestion systems that process structured and unstructured educational content, extracting entities, relationships, and metadata for knowledge base population.
Semantic Parsing & Extraction: Implement NLP pipelines for educational content that extract key concepts, prerequisite relationships, learning objectives, and pedagogical metadata.
Memory & Context Management: Invent and operationalize memory compaction mechanisms, session state management, and cross-conversation memory patterns that allow agents to maintain coherence across extended teaching workflows.
Context Evaluation & Monitoring: Design evaluation frameworks that measure retrieval precision, token relevance, attention allocation, and reasoning coherence as context evolves across sessions.

What we offer

Flexibility of working from home.
Unlimited time off.
Choice of employer-paid health insurance plans. Dental and vision are also offered at very low premiums.
Generous stock options, vested over 4 years.
401k match.
Monthly wellness stipend.

Fulltime

Principal AI Engineer

We are looking for a Principal AI Engineer to lead the design and deployment of ...

Location

United States

Salary:

200000.00 - 300000.00 USD / Year

Apollo.io

Expiration Date

Until further notice

Requirements

10+ years of software engineering experience
at least 3 years in applied LLM or agentic AI systems (2023–present)
proven success in deploying LLM-powered products used by real users at scale
deep backend & systems engineering expertise with Python, distributed systems, and scalable APIs
familiarity with LangChain, LlamaIndex, or similar orchestration frameworks
experience with RAG pipelines, vector DBs, embedding models, and semantic search tuning
experience managing performance across cloud providers (e.g., AWS Bedrock, OpenAI, Anthropic, etc.)
demonstrated experience building multi-step agents, planning workflows, chaining reasoning steps, and integrating APIs with agent memory/state
comfort with advanced prompting strategies, few-shot and chain-of-thought reasoning, and embedding retrieval setups
strong understanding of AI system evaluation, human ratings, A/B experimentation, and feedback loop pipelines

Job Responsibility

Architect and lead the development of multi-agent systems capable of long-horizon planning, reasoning, and API orchestration
build reusable agentic components that integrate deeply into sales and marketing processes
own and evolve our in-house platform for scalable, low-latency, and cost-efficient LLM and agent deployments
lead design of interfaces powered by natural language understanding and retrieval-augmented generation (RAG)
build embedding-based, intent-aware search and personalization systems tuned to business user needs
drive innovation in personalized outreach generation using context-aware generation pipelines
tune inference pipelines, caching layers, and model selection logic for high-scale, cost-aware performance
define and drive robust offline and online testing methodologies (A/B, sandboxing, human evals) across agents and LLM flows
architect human-in-the-loop systems and telemetry to improve accuracy, UX, and explainability over time

What we offer

equity
company bonus or sales commissions/bonuses
401(k) plan
at least 10 paid holidays per year
flex PTO
parental leave
employee assistance program
wellbeing benefits
global travel coverage
life/AD&D/STD/LTD insurance

Fulltime

Senior Context Engineer, AI Systems

MagicSchool is seeking a Senior Context Engineer for AI Systems to design and op...

Location

United States

Salary:

160000.00 - 190000.00 USD / Year

EdTech Jobs

Expiration Date

Until further notice

Requirements

4+ years building distributed systems
Hands-on experience with RAG systems, knowledge graphs, or semantic search platforms in production environments
Strong coding skills in Python, TypeScript/Node.js
Experience with our stack (TypeScript, Node.js, PostgreSQL, NextJS, Supabase) or similar
Proficiency with LLM APIs (OpenAI, Anthropic, etc.) and their context management patterns
Experience with Model Context Protocol (MCP), context window optimization for specific model families, or building context-aware agent frameworks
Understanding of or interest in how educational content is structured (standards, curricula, taxonomies), privacy requirements (FERPA/COPPA), and how context needs differ across teaching scenarios
Experience with agent evaluation, measuring context quality/relevance, or instrumentation for attention budget tracking

Job Responsibility

Architect and optimize how MagicSchool's AI agents reason, remember, and operate within complex educational workflows
Design context management systems that determine what information our agents see, how they maintain state across multi-turn interactions, and how they retrieve knowledge
Implement the technical foundation of how AI agents manage their 'mental workspace'
Design and implement context curation systems for product features
Build memory compaction mechanisms and state management patterns
Implement monitoring and evaluation for retrieval precision and reasoning coherence
Build dynamic, runtime data fetching that enable agents to autonomously pull relevant curriculum content, student data, and educational resources
Build token-efficient tool APIs and retrieval layers for product teams
Partner with Product to translate educational workflows into optimal context configurations
Work with evaluations researchers, platform engineers, and others to implement memory modules, retrieval adapters, and human-in-the-loop correction systems

What we offer

Unlimited time off
Choice of employer-paid health insurance plans
Dental and vision offered at very low premiums
Generous stock options, vested over 4 years
401k match
Monthly wellness stipend

Fulltime

Staff Application Engineer, Workplace Technology

The role is part of the IT Function within the broader Mozilla Infrastructure te...

Location

United States; Canada

Salary:

Not provided

Mozilla

Expiration Date

Until further notice

Requirements

7–10 years of software engineering or automation experience, including experience building scalable systems, integrations and agentic workflows in enterprise environments
Strong software design and development skills in Java, Go, Python, JavaScript/TypeScript (or Apps Script), or equivalent languages
experience with building production-ready services and agentic systems
Deep experience integrating SaaS platforms (collaboration tools, identity systems) using APIs, SDKs, event-driven architectures, and building automation/agent orchestration layers
Familiarity with IAM/SSO (Okta, SAML/OIDC/SCIM), lifecycle automation and securing access across humans and agents
experience embedding governance into automation flows
Proven ability to design for reliability, security, scalability and cost-efficiency
strong experience with observability, metrics and monitoring frameworks for automated/agentic services
Demonstrated ability to lead the technical direction of automation and agentic workflows: build shared libraries, connectors, guide architecture, mentor others, influence cross-team engineering culture
Experience or willingness to work with GenAI/LLM modalities (agent design, prompt management, retrieval + RAG, integrations) and build operational patterns around them (e.g., agent orchestration, trust, guardrails)

Job Responsibility

Architect, develop, and scale automation frameworks, integrations and agentic workflows across Mozilla’s workplace technology ecosystem — including collaboration tools, identity systems (SSO/IAM), and GenAI platforms (OpenAI, Claude, Gemini)
Lead end-to-end engineering of lifecycle workflows (onboarding, off-boarding, access provisioning) using APIs, event-driven architectures and intelligent agentic flows that reduce manual touchpoints and accelerate user access
Build and maintain reusable libraries, connectors, SDKs and agent orchestration layers (e.g., virtual assistants, workflow agents, RAG + retrieval pipelines) that enable faster, safer AI-enabled productivity at scale
Implement observability for agentic workflows and automations: define metrics (SLIs/SLOs), build dashboards, logging, alerts and proactively tune for reliability, security, cost-efficiency and adoption
Partner with Security, Legal, and Privacy to embed DLP, data classification, and least-privilege access into automation and AI flows — ensure agentic capabilities respect governance, auditing, and compliance
Lead evaluation, technical design, and production deployment of new tools and AI productivity platforms: architect integrations, define guardrails, pilot agentic features, measure adoption and user impact
Mentor junior engineers and facilitate collaboration across teams: review design/code, establish best practices for building agentic systems, guide documentation and champion a shared automation culture
Collaborate cross-functionally with IT, Security, Finance, People Ops and Workplace/Facilities to deliver secure, efficient, and scalable internal tools and workflows that empower users and optimize operations
Drive innovation through prototyping next-gen agentic services (for example: intelligent enterprise search assistants, document-to-action bots, contextual collaboration agents) to increase productivity and reduce friction

What we offer

Generous performance-based bonus plans to all eligible employees
Rich medical, dental, and vision coverage
Generous retirement contributions with 100% immediate vesting (regardless of whether you contribute)
Quarterly all-company wellness days where everyone takes a pause together
Country specific holidays plus a day off for your birthday
One-time home office stipend
Annual professional development budget
Quarterly well-being stipend
Considerable paid parental leave
Employee referral bonus program

Fulltime

Staff Application Engineer, Workplace Technology

The role is part of the IT Function within the broader Mozilla Infrastructure te...

Location

United States; Canada

Salary:

Not provided

Mozilla

Expiration Date

Until further notice

Requirements

7–10 years of software engineering or automation experience, including experience building scalable systems, integrations and agentic workflows in enterprise environments
Strong software design and development skills in Java, Go, Python, JavaScript/TypeScript (or Apps Script), or equivalent languages
experience with building production-ready services and agentic systems
Deep experience integrating SaaS platforms (collaboration tools, identity systems) using APIs, SDKs, event-driven architectures, and building automation/agent orchestration layers
Familiarity with IAM/SSO (Okta, SAML/OIDC/SCIM), lifecycle automation and securing access across humans and agents
experience embedding governance into automation flows
Proven ability to design for reliability, security, scalability and cost-efficiency
strong experience with observability, metrics and monitoring frameworks for automated/agentic services
Demonstrated ability to lead the technical direction of automation and agentic workflows: build shared libraries, connectors, guide architecture, mentor others, influence cross-team engineering culture
Experience or willingness to work with GenAI/LLM modalities (agent design, prompt management, retrieval + RAG, integrations) and build operational patterns around them (e.g., agent orchestration, trust, guardrails)

Job Responsibility

Architect, develop, and scale automation frameworks, integrations and agentic workflows across Mozilla’s workplace technology ecosystem — including collaboration tools, identity systems (SSO/IAM), and GenAI platforms (OpenAI, Claude, Gemini)
Lead end-to-end engineering of lifecycle workflows (onboarding, off-boarding, access provisioning) using APIs, event-driven architectures and intelligent agentic flows that reduce manual touchpoints and accelerate user access
Build and maintain reusable libraries, connectors, SDKs and agent orchestration layers (e.g., virtual assistants, workflow agents, RAG + retrieval pipelines) that enable faster, safer AI-enabled productivity at scale
Implement observability for agentic workflows and automations: define metrics (SLIs/SLOs), build dashboards, logging, alerts and proactively tune for reliability, security, cost-efficiency and adoption
Partner with Security, Legal, and Privacy to embed DLP, data classification, and least-privilege access into automation and AI flows — ensure agentic capabilities respect governance, auditing, and compliance
Lead evaluation, technical design, and production deployment of new tools and AI productivity platforms: architect integrations, define guardrails, pilot agentic features, measure adoption and user impact
Mentor junior engineers and facilitate collaboration across teams: review design/code, establish best practices for building agentic systems, guide documentation and champion a shared automation culture
Collaborate cross-functionally with IT, Security, Finance, People Ops and Workplace/Facilities to deliver secure, efficient, and scalable internal tools and workflows that empower users and optimize operations
Drive innovation through prototyping next-gen agentic services (for example: intelligent enterprise search assistants, document-to-action bots, contextual collaboration agents) to increase productivity and reduce friction

What we offer

Generous performance-based bonus plans to all eligible employees
Rich medical, dental, and vision coverage
Generous retirement contributions with 100% immediate vesting
Quarterly all-company wellness days where everyone takes a pause together
Country specific holidays plus a day off for your birthday
One-time home office stipend
Annual professional development budget
Quarterly well-being stipend
Considerable paid parental leave
Employee referral bonus program

Fulltime

Director - AI

The Director -AI in Delivery leads multiple teams and managers, ensuring each gr...

Location

United States

Salary:

168400.00 - 252600.00 USD / Year

3Cloud

Expiration Date

Until further notice

Requirements

12+ years of experience delivering solutions in a primary domain such as application development, cloud platform engineering, DevOps, or data and analytics, including significant work at enterprise scale
7+ years of experience in solution architecture and leading development or engineering teams, including multi-team or multi-workstream efforts at program scale
Proven ability to oversee delivery of complex, enterprise-scale AI/ML programs
Deep expertise across most of the following: Agents & Orchestration – leveraging Semantic Kernel, LangChain, or similar frameworks to design intelligent workflows
applying tool/function calling, planner and agent-based patterns, and workflow automation engines
Search & Retrieval – implementing solutions with vector databases such as Azure AI Search, Pinecone, FAISS, or Milvus
applying hybrid search methods, re-ranking strategies, and selecting embedding models for accuracy and performance
Evaluation, Quality & LLM Operations – establishing offline and online evaluation approaches
using golden datasets, hallucination and groundedness validation, toxicity and safety testing
building telemetry and feedback loops

Job Responsibility

Maintain a clear view of each team member's delivery commitments, growth plans, and internal contributions
Develop and grow team members through regular coaching, clear expectations, and constructive feedback. Build a culture of trust, inclusion, and collaboration
Monitor team health, morale, and workload balance, acting early to address engagement or performance concerns in partnership with practice leadership
Maintain regular one-to-one connections with each team member, provide clear feedback, and help them remove blockers related to client work, pursuits, or internal initiatives
Oversee staffing and resource alignment across teams, balancing utilization, development goals, client needs, and sustainable workloads
Communicate practice priorities and organizational objectives clearly, ensuring teams understand how their work contributes to broader organizational goals
Define interview standards and mentorship strategies, training others to apply them consistently and improving hiring outcomes and talent growth at scale
Create and maintain development plans for team members, including stretch assignments, shadowing, certifications, and opportunities for external visibility
Lead or support performance reviews, promotion recommendations, and compensation input for your teams, using consistent standards that reflect both impact and behavior
Represent your teams in leadership forums, communicate expectations and decisions clearly back to the group, and bring forward patterns, risks, and successes that should shape practice strategy

What we offer

Flexible work location with a virtual first approach to work!
401(K) with match up to 50% of your 6% contributions of eligible pay
Generous PTO providing a minimum of 15 days in addition to 9 paid company holidays and 2 floating personal days
Two medical plan options to allow you the choice to elect what works best for you!
Option for vision and dental coverage
100% employer paid coverage for life and disability insurance
Paid leave for birth parents and non-birth parents
Option for Healthcare FSA, HSA, and Dependent Care FSA
$67.00 monthly tech and home office allowance
Utilization and/or discretionary bonus eligibility based on role

Fulltime

LLM Engineer

You will join our global Machine Learning and Data Science unit — a core team of...

Location

Spain , Barcelona

Salary:

Not provided

Gipo

Expiration Date

Until further notice

Requirements

At least one year of professional experience in LLM development or integration in a fast-paced, product-driven tech environment
Demonstrated expertise in production-grade LLM deployments, including prompt management systems, vector databases, semantic search implementation, and API integration with foundation models
Good understanding of transformer architectures and proficiency in LLM frameworks such as LangChain, LlamaIndex, or similar tools
Proficiency in Python
Experience in collaborative project development
Appreciation for good engineering practices and maintainable code
Proven experience in evaluating LLMs through systematic testing, benchmark design, and the development of custom metrics (e.g. accuracy, consistency, factuality, and bias), with a focus on aligning results to product and user needs
Proven ability to integrate, deploy, and optimize large language models in production-grade industry environments, ensuring scalability and robust performance
Strong knowledge in prompt engineering, agent-based workflows, and the generation and manipulation of embeddings
Experience with RAG (Retrieval-Augmented Generation) techniques, vector similarity search, and information retrieval methods to enhance LLM capabilities

Job Responsibility

Work closely with cross-functional teams, including scientists, engineers, and product stakeholders, to deliver LLM-driven initiatives that directly contribute to business objectives
Design, deploy and iterate over LLM services for text-based applications (and beyond), while proactively identifying and eliminating performance bottlenecks
Build small to medium-sized Python projects and collaborate with engineers on production code and deployments at scale
Assess platform engineering and LLMOps bottlenecks
research and design scalable prompt management strategies, and recommend solutions that balance performance, cost, and reliability
Research, architect, and deploy LLM-powered information retrieval solutions (e.g., RAG) to deliver accurate results in complex, multilingual product environments
Partner with the AI Platform team to refine LLMOps best practices, evolve frameworks, and establish efficient, scalable workflows

What we offer

Flexible remuneration and benefits system via Flexoh, which includes: restaurant card, transportation card, kindergarten, and training tax savings
Share options plan after 6 months of working with us
Remote or hybrid work model with our hub in Barcelona
Flexible working hours (fully flexible, as in most cases you only have to be on a couple of meetings weekly)
Summer intensive schedule during July and August (work 7 hours, finish earlier)
23 paid holidays, with exchangeable local bank holidays
Additional paid holiday on your birthday or work anniversary (you choose what you want to celebrate)
Private healthcare plan with Adeslas for you and subsidized for your family (medical and dental)
Access to hundreds of gyms for a symbolic fee in partnership for you and your family with Wellhub
Access to iFeel, a technological platform for mental wellness offering online psychological support and counseling

Fulltime

LLM Engineer

You will join our global Machine Learning and Data Science unit — a core team of...

Location

Poland , Warsaw

Salary:

Not provided

Gipo

Expiration Date

Until further notice

Requirements

At least one year of professional experience in LLM development or integration in a fast-paced, product-driven tech environment
Demonstrated expertise in production-grade LLM deployments, including prompt management systems, vector databases, semantic search implementation, and API integration with foundation models
Good understanding of transformer architectures and proficiency in LLM frameworks such as LangChain, LlamaIndex, or similar tools
Proficiency in Python
Experience in collaborative project development
Appreciation for good engineering practices and maintainable code
Proven experience in evaluating LLMs through systematic testing, benchmark design, and the development of custom metrics (e.g. accuracy, consistency, factuality, and bias), with a focus on aligning results to product and user needs
Proven ability to integrate, deploy, and optimize large language models in production-grade industry environments, ensuring scalability and robust performance
Strong knowledge in prompt engineering, agent-based workflows, and the generation and manipulation of embeddings
Experience with RAG (Retrieval-Augmented Generation) techniques, vector similarity search, and information retrieval methods to enhance LLM capabilities

Job Responsibility

Work closely with cross-functional teams, including scientists, engineers, and product stakeholders, to deliver LLM-driven initiatives that directly contribute to business objectives
Design, deploy and iterate over LLM services for text-based applications (and beyond), while proactively identifying and eliminating performance bottlenecks
Build small to medium-sized Python projects and collaborate with engineers on production code and deployments at scale
Assess platform engineering and LLMOps bottlenecks
research and design scalable prompt management strategies, and recommend solutions that balance performance, cost, and reliability
Research, architect, and deploy LLM-powered information retrieval solutions (e.g., RAG) to deliver accurate results in complex, multilingual product environments
Partner with the AI Platform team to refine LLMOps best practices, evolve frameworks, and establish efficient, scalable workflows

What we offer

Share options plan after 6 months of working with us
Remote or hybrid work model with or hub in Warsaw
Flexible working hours (fully flexible, as in most cases you only have to be on a couple of meetings weekly)
20/26 days of paid time off (depending on your contract)
Additional paid day off on your birthday or work anniversary (you choose what you want to celebrate)
Private healthcare plan with Signal Iduna for you and subsidized for your family
Multisport card co-financing for you to have access to sports facilities across Poland
Access to iFeel, a technological platform for mental wellness offering online psychological support and counseling
Free English classes

Fulltime

Platform Architect - Search & Retrieval Systems

AlphaSense

Location:
India , Bengaluru

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
January 04, 2026

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