{"id":1621277,"url":"https://alion.io/job/exl-data-scientist-3","title":"Data Scientist","company":{"id":38016,"name":"EXL","domain":"exlservice.com","url":"https://alion.io/company/exl","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":75,"open_postings":54,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-03T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Noida, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":18500,"max_usd":38000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":51},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Apache Kafka","optional":false},{"name":"Apache Pulsar","optional":false},{"name":"AutoGen","optional":false},{"name":"Embeddings","optional":false},{"name":"FastAPI","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"LangChain","optional":false},{"name":"Langfuse","optional":false},{"name":"LangGraph","optional":false},{"name":"LangSmith","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Pinecone","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Pydantic","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"WebSockets","optional":false},{"name":"Claude","optional":true},{"name":"Prompt Engineering","optional":true}],"status":"live","first_seen_at":"2026-09-29T14:39:46Z","employer_posted_date":"2026-09-29","last_verified_at":"2026-10-03T22:57:46Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Key Responsibilities\nLeadership & Strategy\nLead architectural design and implementation of multi-agent AI systems\nDrive technical strategy for GenAI initiatives and recommend best practices\nMentor and provide technical guidance to junior and mid-level engineers\nCollaborate with stakeholders to define requirements and deliver solutions\nOwn end-to-end delivery of complex, production-scale AI systems\nTechnical Execution\nBuild and maintain high-performance REST/WebSocket APIs using FastAPI (Pydantic v2)\nImplement and optimize agentic AI systems using frameworks like LangGraph, Deep Agents, AutoGen, and LangChain\nArchitect real-time, event-driven microservices using messaging queues like Apache Kafka \nDesign clean, testable, maintainable services using SOLID principles, Python async, and type hints\nIntegrate and optimize SQL, NoSQL, and vector databases (Postgres, MongoDB, ChromaDB, Pinecone)\nRun LangGraph/Deep Agents workflows in production with checkpointing, persistence, and human-in-the-loop controls, backed by LLM observability and evaluation tooling (e.g., LangSmith, Langfuse)\nApply LLM safety guardrails (prompt-injection mitigation, PII handling, content moderation) in line with Banking, Insurance, and Healthcare compliance requirements\nStay current with emerging trends in GenAI, deep learning, and AI orchestration framework\nSkills and Competencies\nProven ability to architect and deliver end-to-end GenAI solutions and multi-agent systems\nStrong software engineering discipline: testing (unit, integration, performance), code review, documentation\nExcellent communication skills with ability to explain complex technical concepts to non-technical stakeholders\nStrategic thinking and problem-solving with a focus on scalability and maintainability\nLeadership capability: mentoring, technical guidance, and cross-functional collaboration\n\n Key Responsibilities\nLeadership & Strategy\nLead architectural design and implementation of multi-agent AI systems\nDrive technical strategy for GenAI initiatives and recommend best practices\nMentor and provide technical guidance to junior and mid-level engineers\nCollaborate with stakeholders to define requirements and deliver solutions\nOwn end-to-end delivery of complex, production-scale AI systems\nTechnical Execution\nBuild and maintain high-performance REST/WebSocket APIs using FastAPI (Pydantic v2)\nImplement and optimize agentic AI systems using frameworks like LangGraph, Deep Agents, AutoGen, and LangChain\nArchitect real-time, event-driven microservices using messaging queues like Apache Kafka \nDesign clean, testable, maintainable services using SOLID principles, Python async, and type hints\nIntegrate and optimize SQL, NoSQL, and vector databases (Postgres, MongoDB, ChromaDB, Pinecone)\nRun LangGraph/Deep Agents workflows in production with checkpointing, persistence, and human-in-the-loop controls, backed by LLM observability and evaluation tooling (e.g., LangSmith, Langfuse)\nApply LLM safety guardrails (prompt-injection mitigation, PII handling, content moderation) in line with Banking, Insurance, and Healthcare compliance requirements\nStay current with emerging trends in GenAI, deep learning, and AI orchestration framework\nSkills and Competencies\nProven ability to architect and deliver end-to-end GenAI solutions and multi-agent systems\nStrong software engineering discipline: testing (unit, integration, performance), code review, documentation\nExcellent communication skills with ability to explain complex technical concepts to non-technical stakeholders\nStrategic thinking and problem-solving with a focus on scalability and maintainability\nLeadership capability: mentoring, technical guidance, and cross-functional collaboration\n\n Minimum Qualifications\nBachelor's degree in Computer Science, Data Science, or related field\n5+ years of total professional experience, including:\n3+ years of hands-on Software Engineering experience in Python, FastAPI and relevant tech stack\n2+ years working specifically with GenAI and LLMs (GPT, Claude, LLaMA, etc.)\nTrack record of shipping production ML/AI products, with strong prompt-engineering skills, systems-level thinking, and the ability to diagnose and resolve production failures\nStrong software engineering background with expertise in OOP and SOLID principles\nProficiency in Python 3.11+ (async/await, type hints, modern Python patterns, strict type checking)\nExperience with agentic frameworks (LangChain, LangGraph, AutoGen, or similar)\nProven track record building production REST/WebSocket APIs and microservices\nExperience with message streaming platforms (Kafka, Pulsar, or similar)\nStrong knowledge of databases: SQL, NoSQL, and vector databases\nWorking knowledge of RAG pipelines (embeddings, chunking, retrieval) and LLM observability/evaluation tools (LangSmith, Langfuse, or similar)","description_format":"text","description_chars":4837,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-10-01T20:44:33Z"}],"visa":[],"liveness":{"score":70,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.695,"p_room":1,"age_days":3,"expected_fill_days":22,"reasons":["conf:4","stale_co","wave","velocity","win:early","comp:brand"],"computed_at":"2026-10-03T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/exl-data-scientist-3","json_url":"https://alion.io/job/exl-data-scientist-3.json","meta":{"generated_at":"2026-10-04T00:37:59Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":726,"day_limit":5000,"remaining_today":4274,"minute_limit":60,"resets_at":"2026-10-05T00:00:00Z"}}}