Senior Software Engineer (AI)

Role Overview: Senior Software Engineer (AI) will design, build, and ship production-ready AI and LLM-powered applications. The role combines strong backend engineering with hands-on generative AI expertise—developing RAG pipelines, intelligent APIs, agentic workflows, and scalable cloud deployments while collaborating across product, data, design, and engineering teams Key focus areas 1. AI and LLM engineering LLM integration: Build applications on large language models such as Azure OpenAI, OpenAI, Anthropic or open-source models. This includes prompt design, function and tool calling, and structured outputs. RAG (retrieval-augmented generation): Design retrieval pipelines that cover document ingestion, chunking, embeddings, vector search, re-ranking and grounding responses in trusted sources. AI agents and orchestration: Build agentic workflows using Claude/Co-pilot/Gemini. Evaluation and guardrails: Set up evaluation frameworks that measure accuracy, hallucination rate, latency and cost. Add safety filters, PII handling and content moderation. 2. Python and backend development Python: Strong skill in Python/Java/Php for AI development, including async programming, type hints and packaging. API development: Build RESTful APIs (FastAPI, Flask or ASP.NET Core) that expose AI features, with streaming responses, serialization and versioning. Application architecture: Understanding of dependency injection, middleware, configuration and clean, maintainable project structure. 3. Data and storage SQL: Strong skill in SQL, including joins, query optimization and working with Microsoft SQL Server. Vector databases: Hands-on experience with Azure AI Search, Pinecone or similar. Data pipelines: Prepare, clean and transform structured and unstructured data (PDFs, documents, logs) for AI workloads. 4. Communication Strong communication skills, including the ability to explain AI capabilities, limitations and trade-offs to technical and non-technical stakeholders. Also required ML fundamentals: Understanding of embeddings, tokenization, fine-tuning, model selection and the basics of how transformers work. Cloud and MLOps: Design and deploy AI solutions on Azure (preferred), AWS or GCP. Experience with Azure AI Foundry or Azure ML, containerization (Docker, Kubernetes), CI/CD for AI services, and model and prompt versioning. Performance and scalability: Optimize AI systems for latency, throughput and token cost through caching, batching, concurrency and rate-limit handling. Queue management: Design message queues for reliable, asynchronous AI processing pipelines and communication between services. Collaboration: Work closely Product Owners, data teams, designers and front-end developers to turn business problems into AI solutions. Code review and mentoring: Review code, give constructive feedback, and mentor junior engineers on AI engineering best practices. Must have 4+ years of software development experience, with 1+ years in AI/ML or LLM-based applications Strong skill in Python/Java/Php Hands-on experience with LLM APIs, prompt engineering and RAG architectures Experience with Azure cloud services, especially Azure OpenAI and Azure AI Search Proficiency in Microsoft SQL Server and at least one vector database Experience shipping AI features to production, not just prototypes Excellent verbal and written communication skills, with the ability to explain complex ideas clearly Skills: Java,Python, LLMs, RAG, Prompt Engineering, Azure OpenAI, Vector Databases, SQL Server, Communication and Articulation Good to have Experience with Angular or React for building AI-powered user interfaces, such as chat UIs and streaming responses Familiarity with WebSockets or Server-Sent Events for real-time AI responses Experience fine-tuning models or with open-source LLMs (Hugging Face, Ollama, vLLM) Knowledge of MCP (Model Context Protocol) and multi-agent systems Experience with RabbitMQ, Azure Service Bus or Kafka Qualifications Bachelor’s or master’s degree in Computer Science, AI/ML, Data Science, Information Technology or a related field (or equivalent experience)