Sr Engineer - AI COE

Tata Communications Redefines Connectivity with Innovation and IntelligenceDriving the next level of intelligence powered by Cloud, Mobility, Internet of Things, Collaboration, Security, Media services and Network services, we at Tata Communications are envisaging a New World of Communications

• *Job Title:**

Sr. Engineer (ML Engineer/Data Engineer)

• *Role Summary:**

We are hiring a Sr. Engineer (2\+ years) for the AI CoE to build and deploy Generative AI, RAG, Agentic AI, Machine Learning \& Data Engineering solutions. This role combines LLM\-driven applications with strong ML fundamentals, supporting scalable and monetizable AI products for telecom and enterprise use cases.

• *Key Responsibilities:**

• Build and deploy LLM\-based applications, RAG, and Agentic RAG systems
• Build optimized data pipeline to support AI applications

• Develop multi\-agent workflows using tools like LangChain, LlamaIndex, **LangGraph** , Azure, and AWS Bedrock
• Integrate MCP tools, APIs, and function\-calling into AI systems
• Design prompting strategies, embeddings, and vector search pipelines using **Milvus / FAISS / Pinecone**
• Implement **structured output generation** for LLM responses (JSON/schema\-driven outputs)
• Apply machine learning techniques (classification, clustering, predictive modeling) for telecom and enterprise use cases
• Perform data preprocessing, feature engineering, and model evaluation
• Optimize solutions for performance, scalability, cost, and latency
• Develop backend APIs using **FastAPI** for serving AI/ML models
• Containerize applications using **Docker** for scalable deployment
• Implement monitoring, logging, and observability using **Grafana and ELK stack**
• Enable LLM traceability and observability using **Langfuse etc.**
• Collaborate with product and engineering teams to deliver production\-grade AI solutions
• *Required Skills:**
• 2\+ years of experience in Data Engineering / AI / Machine Learning /Gen AI
• Excellent proficiency in Python and working knowledge of SQL ( **PostgreSQL preferred** )
• Hands on Data Engineering experience with big data tools and technology.

• Hands\-on experience with Machine Learning algorithms and model development
• Strong understanding of ML concepts: supervised/unsupervised learning, feature engineering, model evaluation, bias\-variance tradeoff
• Hands\-on experience with LLMs, Generative AI, RAG architectures, and **Agentic workflows**
• Experience with LangChain / LlamaIndex / **LangGraph** / vector databases ( **Milvus, FAISS, Pinecone** )
• Experience building APIs using **FastAPI**
• Understanding of **structured output handling in LLMs**

• **Good to Have:**
• Exposure to MCP tools and LLM orchestration frameworks
• Experience with Agentic AI / multi\-agent systems
• Cloud experience (Azure / AWS / GCP)
• Experience with **Langfuse (LLM tracing \& monitoring)**
• Familiarity with **Grafana, ELK stack for monitoring**
• Experience with **Docker\-based deployments****Key Focus Areas:**
• Agent\-based chatbots \& virtual assistants
• Data pipelines

• RAG\-based knowledge systems
• Multi\-agent automation workflows ( **LangGraph\-based** )
• ML\-driven use cases (prediction, recommendation, analytics) in telecom
• Scalable AI APIs and microservices using FastAPI
• *Additional Note:**

Role involves hands\-on Python coding and system design assessments, covering machine learning fundamentals, model building, RAG, LLMs, agent\-based applications, **LangGraph workflows** , API development, and production deployment considerations (Docker, monitoring, traceability).