Full-Stack AI Engineer

2 days ago

Gurgaon, Haryana, India Fia Technology Services Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Full-Stack AI Engineer (ML/DL, GenAI, LLMs, Agentic AI)

About the role

Were building intelligent systems that move from insight to action—at scale. As a Full-Stack AI Engineer, you'll design, ship, and own AI products that blend cutting-edge research (LLMs, Generative AI, Agentic workflows) with real-world impact. You'll work end-to-end: from data pipelines and model training to robust APIs, delightful UIs, and cloud-native deployments that serve thousands of users reliably.

What you'll do

  • Design, train, and ship ML/DL/GenAI models (LLMs, diffusion, retrieval-augmented generation) for production use cases.
  • Build agentic systems: autonomous/goal-driven agents, tool-use, planning, memory, and multi-step orchestration.
  • Own the full stack: data ingestion/ETL feature stores model serving backend APIs (REST/GraphQL) lightweight frontends/SDKs.
  • Operationalize models: containerize (Docker), orchestrate (Kubernetes), instrument monitoring (latency, drift, hallucinations), and automate CI/CD.
  • Collaborate cross-functionally with Product, Design, Data, Security, and Compliance to refine requirements, experiment, and iterate quickly.
  • Scale systems in the cloud (Azure): design for reliability, observability, and cost-efficiency.
  • Champion quality & safety: evaluation harnesses, red-team testing, guardrails, prompt/finetune hygiene, and privacy-by-design.
  • Document and mentor: write clear specs, contribute to internal tooling, and share best practices.

Tech you'll use (and/or quickly learn)

Languages: Python (must-have), plus for services; familiarity with React is a plus.

Frameworks: PyTorch/TensorFlow/JAX; LangChain/LlamaIndex/Guidance; Ray/Accelerate/Lightning for distributed training.

LLM/GenAI stack: OpenAI/Anthropic/Google/Meta models, LoRA/QLoRA, RAG, vector DBs (FAISS, Milvus, Pinecone), prompt engineering & finetuning.

MLOps: MLflow/W&B, Feast, Airflow/Prefect, Triton/TorchServe/FastAPI, feature stores, experiment tracking, model registries.

Cloud/Infra: AWS (S3, EKS, SageMaker, Lambda) or GCP (GCS, GKE, Vertex AI), Terraform, Kubernetes, Docker, Redis/Kafka/Postgres.

Security/Compliance: secrets management, VPC/isolation, audit logging, PII handling, role-based access.

What you bring

  • 5 years building production systems, including 3+ years with ML/DL and hands-on experience with LLMs/GenAI.
  • Proven track record deploying models to production and supporting them (SLOs, on-call, post-mortems).
  • Strong software engineering foundations: testing, code reviews, design patterns, performance profiling.
  • Experience designing RAG/agentic pipelines, tool integration (function calling), and evaluation frameworks.
  • Comfortable with ambiguous problem spaces; able to turn business goals into measurable technical plans.
  • Soft skills: ownership mindset, crisp communication, collaborative spirit, bias for action, and a product mindset.

Nice-to-have

  • Advanced degree in CS/EE/Stats/Applied Math—or equivalent applied experience.
  • Domain expertise in fintech, risk, fraud detection, document understanding, or workflow automation.
  • Experience with streaming data, graph ML, reinforcement learning, or multimodal (text-vision-audio).
  • Contributions to open-source AI or published research.

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