AI Engineer / Developer

AI Engineer + Data Scientist
JD
AI Engineer / Developer
Snapshot
Experience: 5–7 years in ML/AI engineering
Reports To: AI Technical Lead / Manager, AIML
Education: B.E./B.Tech or M.Tech in CS, Data Science, or related field
About The Role
Build and ship production-grade GenAI and agentic AI applications that automate enterprise workflows — from design through deployment. A hands-on individual-contributor role for a strong builder.
Key Responsibilities
Build agentic applications using LangGraph, AutoGen, CrewAI, or Semantic Kernel.
Design RAG pipelines — chunking, hybrid search, re-ranking, memory, and tool orchestration.
Deploy and monitor AI workloads on Azure (AKS/ARO) with CI/CD and observability.
Implement responsible-AI guardrails — prompt-injection defense and content filtering.
Define evaluation metrics for task success, hallucination, latency, and cost.
Must-Have Skills
5+ years ML/AI engineering with production LLM/agentic delivery.
Advanced Python and at least one agent framework (LangGraph, AutoGen, CrewAI, PydanticAI).
Strong LLM and prompt-engineering skills (GPT, Claude, LLaMA); hands-on RAG workflows.
Azure AI stack (Azure OpenAI, AI Search, AI Services) and Databricks ML (MLflow, Delta Lake).
Vector databases (FAISS, Pinecone, Chroma) and embedding/retrieval design.
Containerized deployment (Docker/Kubernetes, AKS/ARO) and REST APIs / WebSockets / event-driven services.
CI/CD and version control (Jenkins / GitHub Actions, Git) with SDLC and agile practices.
Portfolio of 3+ production AI deployments with measurable business impact.
Nice to Have
Model fine-tuning (LoRA/PEFT), multi-modal AI, and model evaluation frameworks.
LLMOps / MLOps and model monitoring (drift, latency, cost, hallucination).
Knowledge graphs (Neo4j); AWS Bedrock / GCP Vertex AI exposure.
AI-augmented dev tools (GitHub Copilot, Claude Code, Windsurf) for rapid prototyping.
Enterprise AI security, compliance, and governance awareness.
Manufacturing or supply-chain domain experience.
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AI Engineer + Data Scientist - Lead
JD
AI Technical Lead
Snapshot
Experience: 8+ years in ML/AI (incl. DL/RL in production)
Reports To: Manager, AIML
Education: Master's (preferred) or Bachelor's in CS, Data Science, or Mathematics
About The Role
Own the full lifecycle of enterprise-scale AI solutions — architecture through production — and set technical best practices, governance, and standards across the team. A player-coach leadership role.
Key Responsibilities
Architect end-to-end DL/RL and agentic AI solutions from design to production.
Set technical standards, governance, and evaluation frameworks across the team.
Optimize models for production inference (TensorRT/ONNX/Triton); balance accuracy vs. latency.
Scale training/inference on Azure ML, AKS/ARO, and distributed infrastructure.
Lead technical solutioning, manage stakeholders, and mentor engineers.
Must-Have Skills
7+ years ML/AI with production DL and/or RL systems.
Mastery of DL frameworks (PyTorch/TensorFlow/JAX) and strong applied math (linear algebra, probability, optimization).
Deep learning across CNNs, transformers, and sequence models; RL agents (PPO, SAC, TD3, CQL).
Inference optimization (TensorRT/ONNX/Triton) and accuracy vs. latency benchmarking.
Model serving and containerized deployment at scale (Docker/Kubernetes, AKS/ARO).
Cloud-scale training/inference on Azure ML with distributed training and MLOps/CI-CD.
Ability to define standards, governance, and evaluation frameworks across a team.
Proven technical leadership, mentoring, and stakeholder communication.
Track record of 6–10 production deployments with measurable business impact.
Nice to Have
Agentic AI architecture (LangGraph, AutoGen, CrewAI) and RAG pipeline design.
RL libraries (Ray RLlib, Stable-Baselines3, Gymnasium); multi-agent RL and simulation (MuJoCo).
Model compression/quantization and GPU-efficiency optimization.
Agentic platform evaluation (Azure AI Foundry, AWS Bedrock, Databricks AgentBricks).
Optimization/OR background (LP/MIP, Gurobi/CPLEX); Julia/SciML exposure.
Semiconductor, manufacturing, or supply-chain domain experience.
Skills: cd,azure,ml,optimization

Work arrangement
No