Senior Software Engineer - AI Forward Deployed Engineer

About the role

AT&T is hiring a Senior Software Engineer (AI Forward Deployed Engineer) in Bengaluru, India. The role works with business and technical stakeholders to turn AI requirements into production-ready solutions, designing and building Generative AI, RAG, advanced RAG and agentic AI applications, and integrating them with enterprise systems.

Key responsibilities

• Identify high-value AI use cases and turn ambiguous requirements into production-ready solutions.
• Design and build Generative AI, RAG, advanced RAG and agentic AI applications.
• Build retrieval pipelines (ingestion, parsing, chunking, embeddings, indexing, hybrid retrieval, reranking, grounding, response generation).
• Develop single- and multi-agent systems with planning, reasoning, tool calling, workflow orchestration, memory and human-in-the-loop approvals.
• Integrate Model Context Protocol (MCP) servers and clients, and build reusable tools, plugins, APIs and connectors.
• Develop AI-enabled backend services and microservices in Python, FastAPI, Flask, REST and event-driven patterns.
• Apply prompt and context engineering, and build automated evaluation pipelines for retrieval quality, hallucination, latency, security and cost.
• Implement LLMOps/GenAIOps, AI security guardrails and responsible AI practices.
• Turn validated prototypes into secure, scalable enterprise applications and troubleshoot complex issues.

Required profile

• 8+ years of software, cloud, AI/ML, platform or solution engineering experience, including production-grade Generative AI, RAG or Agentic AI systems.
• Strong Python programming and hands-on experience with Generative AI and LLM applications on Azure OpenAI, OpenAI or equivalent platforms.
• Experience with RAG, agentic AI, prompt/context engineering, embeddings, vector search and AI evaluation.
• Knowledge of AI security risks (OWASP Top 10 for LLM apps) and identity/access controls (OAuth 2.0, OIDC, RBAC, Key Vault).
• Git, CI/CD, Docker and Kubernetes (preferred); good debugging and stakeholder communication skills.

Required skills

• Python, FastAPI, Flask, REST, JSON, async programming and message queues
• RAG, embeddings, vector search, Azure AI Search, pgvector, Redis, Pinecone, Qdrant, Weaviate
• Semantic Kernel, LangChain, LangGraph, AutoGen
• Azure services, Git, GitHub Actions or Azure DevOps, Docker, Kubernetes (preferred)
• Good to have: Graph RAG, multimodal AI, model fine-tuning, MLflow, LangSmith, Terraform, Playwright, GitHub Copilot