Technical Specialist - Application Development with AI/ML Focus (Pune)

Technical Specialist-App Development Area(s) of responsibility Develop, configure, and deploy AI agents using Aiseras platform and comparable agentic AI toolsets to solve real-world client workflows. Build autonomous and multi-agent systems capable of planning, reasoning, tool selection, and task execution. Design and implement RAG pipelines, function/tool calling, memory and context management, and agent orchestration. Integrate agents with external systems APIs, webhooks, databases, CRMs, ITSM platforms, and data pipelines for seamless workflow execution. Apply prompt engineering and configuration tuning to optimize agent accuracy, latency, and cost in complex enterprise environments. Translate business requirements into functional and technical agent designs; run interactive demos and PoCs and iterate on feedback. Build scalable backend services/microservices for AI applications; ensure testing, monitoring, and CI/CD best practices. Implement AI governance, security, and compliance controls (auth flows, responsible-AI safeguards, observability of agent behavior). Troubleshoot, monitor, and continuously improve deployed agents using data-driven evaluation (A/B testing, performance monitoring). Required Skills & Experience 812 years in software development, AI/ML engineering, or systems integration, with recent hands-on Agentic AI / LLM delivery. Hands-on experience with Aisera or comparable agentic AI / conversational AIOps platforms (ServiceNow AI Agents, Automation Anywhere, similar). Strong programming in Python (primary), plus Java and/or JavaScript; clean, efficient, production-quality code. Proven experience building agents with LLM frameworks LangChain, LangGraph, CrewAI, AutoGen, or PydanticAI. Solid understanding of LLMs, embeddings, vector databases, RAG, function calling, and agent evaluation. Experience with Model Context Protocol (MCP) and multi-agent architectures (preferred). Integration experience: REST APIs, webhooks, data pipelines; OAuth/OIDC/JWT authorization flows. Cloud & DevOps: AWS, Azure, or GCP, containerization (Docker/Kubernetes), CI/CD, and monitoring. Familiarity with AI/LLM observability tooling (Langfuse, ELK) is highly desirable. Solid problem-solving, customer-facing communication, and the ability to work independently. Qualifications Bachelors or Masters in Computer Science, AI, Data Science, or a related field. Relevant cloud/AI certifications are a plus. Knowledge of AI governance frameworks (e.g., ISO/IEC 42001) is a nice-to-have .