Role: AI Engineer

Desired Experience Range: 5-10 years

Location: Chennai, Hyderabad, Gurugram

Roles Responsibilities-

- Build and ship production-ready AI/ML featuresfrom data ingestion and feature engineering to model
- training, evaluation, and deployment.
- Develop LLM/GenAI solutions (prompt engineering, tool use, guardrails) and RAG pipelines (chunking,
- embeddings, vector search, caching, re-ranking).
- Optimise training and inference performance via batching, quantisation, distillation, LoRA/PEFT, accelerator
- utilisation (GPU/TPU), and efficient memory/latency tuning.
- Build and maintain MLOps/LLMOps workflowsCI/CD for models and prompts, model registry/versioning,
- feature stores, and automated promotion across environments.
- Instrument observability for data, models, and prompts (telemetry, metrics, traces, dashboards, alerts);
- implement A/B tests and online/offline evaluation.
- Embed Responsible AI considerations (fairness, explainability, safety, bias testing) and document
- assumptions, datasets, and limitations.
- Document architecture, workflows, and best practices to support scalability and ongoing maintainability.
- Conduct code reviews, write unit/integration/e2e tests (including data and prompt tests), and uphold
- engineering standards and documentation.
- Work with advanced AI/ML frameworks, cloud services, and container orchestration platforms.
- As an AI Engineer, you are responsible for designing, building, and deploying scalable AI and machine
- learning solutions that solve realworld business problems, partnering closely with data scientists to
- productionize models and integrate them seamlessly into applications and enterprise workflows
- Hands-on experience with GenAI, Gemini or Open source LLMs , Train , finetune and Onboard new LLMs
- Experience in building GenAI applications using Python




- Hands-on Experience with API Development and Microservices architecture and End to End integrations
- Knowledge of RAG (Retrieval-Augmented Generation ) and ADK, MCP
- Solid understanding of LLMs, prompt engineering, and graph-based workflows.
- Hands-on Experience with API Development and Microservices architecture
- Experience in CI/CD pipelines, and containerization (Docker/Kubernetes)., Harness and Git actions
- Practical experience implementing LLM and GenAI solutions, including prompt engineering, model
- fine-tuning, RAG pipelines, embeddings, and vector databases.
- Build scalable data pipelines and workflows on GCP (Big Query, Vertex AI, Dataflow, Pub/Sub, Redis and
- NoSQL Databases , Maintaining chat history etc.
- Optimize model performance, monitor production systems, and ensure reliability , Auto Scaling using
- Prometheus, Dynatrace and Lang Smith
- Robust hands-on experience building and deploying machine learning models, including preprocessing,
- feature engineering, training, evaluation, and optimisation.
- Knowledge of API Gateways and ISTIO , ability to Diagnose and intercept failures in End to End
- communication.
- Implement best practices for data governance, security, and MLOps on GCP.
- Proficiency with Python and common AI/ML frameworks such as TensorFlow, PyTorch, JAX, scikit-learn, and
- Hugging Face libraries.
- Knowledge of MLOps and LLMOps practicesincluding CI/CD for models, model registry/versioning, feature
- stores, orchestration, and automated deployments.
- Ensure AI solutions meet security, privacy, compliance, and responsible AI standards.
- Understanding of secure engineering and data protection practices, including IAM, secrets management,
- encryption, and safe handling of sensitive data.
- Ability to optimise performance of training and inference pipelinesprofiling, quantisation, distillation,
- batching, caching, or hardware acceleration.
- Collaborate with data scientists to productionize models and integrate them into applications, workflows, and APIs.

📌 Artificial Intelligence Engineer (Hyderabad)
🏢 Tata Consultancy Services
📍 Hyderabad