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Agentic AI - Manager

Fresher   Gurugram   30 Oct, 2025
Taggd
Job LocationGurugram
EducationNot Mentioned
SalaryNot Disclosed
IndustryIT Services & Consulting
Functional AreaEmbedded / System Software
EmploymentTypeFull-time

Job Description

    Location:GurgaonFunction:EngineeringReports to:CTOTeam size:78 engineers (startup pod)Why this roleWere building enterprisegradeAgentic AI platform & applications for recruitmentfrom sourcing and screening to interview assistance and offer orchestration. Youll lead a small, highleverage team that ships fast, measures rigorously, and scales responsibly.What youll do
    • Own delivery endtoend:backlog, execution, quality, and timelines for Agentic AI features.
    • Be handson (3050% coding):set the technical bar in Python/TypeScript; review PRs; unblock tricky problems.
    • Design agentic systems:tooluse orchestration, planning/looping, memory, safety rails, and cost/perf optimization.
    • Leverage LLMs smartly:RAG, structured output, function/tool calling, multimodel routing; evaluate build vs. buy.
    • Ship production ML/LLM workflows:data pipelines, feature stores, vector indexes, retrievers, model registries.
    • MLOps & Observability:automate training/inference CI/CD; monitor quality, drift, toxicity, latency, cost, and usage.
    • EVALs & quality:define tasklevel metrics; set up offline/online EVALs (goldens, rubrics, humanintheloop) and guardrails.
    • DevOps (Tshaped):own pragmatic infra with the teamGitHub Actions, containers, IaC, basic K8s; keep prod healthy.
    • Security & compliance:enforce data privacy, tenancy isolation, PII handling; partner with Security for audits.
    • People leadership:recruit, coach, and grow a hightrust team; establish rituals (standups, planning, postmortems).
    • Stakeholder management:partner with Product/Design/Recruitment SMEs; translate business goals into roadmaps.
    What youve done (musthaves)
    • 10 years in software/ML; 4 years leading engineers (TL/EM) in highvelocity product teams.
    • Built and operatedLLMpoweredor ML products at scale (userfacing or enterprise workflows).
    • Strong coding inPython, JavaandTypeScript/Node; solid system design and API fundamentals.
    • Exposure tofrontendtechnologies like React, Angular, Flutter
    • Experience on SQL databases like Postgres, MariaDB
    • PracticalMLOps: experiment tracking, model registries, reproducible training, feature/vectors, A/B rollouts.
    • LLM tooling: orchestration (LangChain/LlamaIndex/DSPy), vector DBs (pgvector/FAISS/Pinecone/Weaviate), RAG patterns, context engineering
    • Observability & EVALs: ML/LLM monitoring, LLM eval frameworks (RAGAS/DeepEval/OpenAI Evals), offlineonline testing and human review.
    • Comfortable withDevOps: GitHub Actions, Docker, basic Kubernetes, IaC (Terraform), and one major cloud (GCP/AWS/Azure).
    • Familiar withAI SDLC tools: GitHub Copilot, Cursor, Claude Code, Code Llama/Codexstyle tools; test automation.
    • Product mindset: measure outcomes (quality, cost, speed), not just outputs; datadriven decisions.
    Nice to have
    • HRTech/recruitment domain (ATS/CRM, assessments, interview orchestration).
    • Retrieval quality tuning, promptengineering at scale, policy/guardrail systems (OpenAI/Guardrails/NeMo Guardrails).
    • Knowledge ofmultiagentframeworks, graph planners, or workflow engines (Prefect/Temporal).
    • Experience withprivacy preserving ML, tenancy isolation, regionalization.

Keyskills :
pythonnlp

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