AI Platform Engineering Lead
TaggdHaryāna, Republic Of India, IN9 hours ago
Job descriptionDesign agentic systems : tool‑use orchestration, planning / looping, memory, safety rails, and cost / perf optimization. Leverage LLMs smartly : RAG, structured output, function / tool calling, multi‑model routing; Ship production ML / LLM workflows : data pipelines, feature stores, vector indexes, retrievers, model registries. MLOps & Observability : automate training / inference CI / CD; EVALs & quality : define task‑level metrics; DevOps (T‑shaped) : own pragmatic infra with the team—GitHub Actions, containers, IaC, basic K8s; Security & compliance : enforce data privacy, tenancy isolation, PII handling; People leadership : recruit, coach, and grow a high‑trust team; Stakeholder management : partner with Product / Design / Recruitment SMEs; 10+ years in software / ML; Built and operated LLM‑powered or ML products at scale (user‑facing or enterprise workflows). Strong coding in Python, Java and TypeScript / Node ; Exposure to frontend technologies like React, Angular, Flutter Experience on SQL databases like Postgres, MariaDB Practical MLOps : 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), offline+online testing and human review. Comfortable with DevOps : GitHub Actions, Docker, basic Kubernetes, IaC (Terraform), and one major cloud (GCP / AWS / Azure). Familiar with AI SDLC tools : GitHub Copilot, Cursor, Claude Code, Code Llama / Codex‑style tools; Product mindset : measure outcomes (quality, cost, speed), not just outputs; HRTech / recruitment domain (ATS / CRM, assessments, interview orchestration). Retrieval quality tuning, prompt‑engineering at scale, policy / guardrail systems (OpenAI / Guardrails / NeMo Guardrails). Knowledge of multi‑agent frameworks, graph planners, or workflow engines (Prefect / Temporal). Experience with privacy‑preserving ML , tenancy isolation, regionalization.
Engineering Manager - Agentic AI
Location : Gurgaon
Function : Engineering
Reports to : CTO
Team size : 7–8 engineers (startup pod)
Why this role
We’re building enterprise‑grade Agentic AI platform & applications for recruitment —from sourcing and screening to interview assistance and offer orchestration. You’ll lead a small, high‑leverage team that ships fast, measures rigorously, and scales responsibly.
What you’ll do
- Own delivery end‑to‑end : backlog, execution, quality, and timelines for Agentic AI features.
- Be hands‑on (30–50% coding) : set the technical bar in Python / TypeScript;
- review PRs;
unblock tricky problems.
evaluate build vs. buy.
monitor quality, drift,toxicity, latency, cost, and usage.
set up offline / online EVALs (goldens, rubrics, human‑in‑the‑loop) and guardrails.
keep prod healthy.
partner with Security for audits.
establish rituals (standups, planning, postmortems).
translate business goals into roadmaps.
What you’ve done (must‑haves)
4+ years leading engineers (TL / EM) in high‑velocity product teams.
solid system design andAPI fundamentals.
test automation.
data‑driven decisions.
Nice to have
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Platform Engineering Lead • Haryāna, Republic Of India, IN
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