Position Summary

We are seeking an experienced Expert AI Agentic Developer to design, develop, and deploy advanced AI agent-based solutions. The ideal candidate will have strong expertise in Agentic AI architectures, Generative AI, LLMOps, cloud deployment, and enterprise integrations. This role requires building scalable, secure, and production-ready AI applications while ensuring Responsible AI, governance, and business alignment.

Key Responsibilities

Must Have

Design, develop, and deploy AI agent-based applications for enterprise use cases.

Build and optimize Agentic AI workflows, including Planner-Executor, Tool Calling, Multi-Agent Systems, and Human-in-the-Loop architectures.

Develop scalable AI solutions using Python with strong coding, testing, and version control practices.

Integrate and utilize Large Language Models (LLMs) and Generative AI frameworks such as OpenAI, LangChain, LangGraph, AutoGen, or similar technologies.

Implement LLMOps practices, including model evaluation, prompt optimization, experimentation, performance monitoring, and performance tuning.

Ensure AI Governance, Responsible AI, and Guardrails through prompt safety, input/output validation, privacy controls, and risk management.

Integrate AI solutions with REST APIs, enterprise systems, business applications, and internal/external tools.

Deploy, manage, and optimize AI applications within AWS cloud environments.

Utilize Docker, Kubernetes, and CI/CD pipelines for deployment automation and scalability.

Work with data platforms such as Snowflake for retrieval, grounding, context management, and AI-powered solutions.

Collaborate with stakeholders to translate business requirements into AI solutions and measurable KPIs.

Good to Have

Experience in Private Banking, Asset & Wealth Management (AWM), Banking, or Financial Services domains.

Experience designing and deploying Retrieval-Augmented Generation (RAG) solutions.

Knowledge of Vector Databases such as Pinecone, Weaviate, Chroma, or FAISS.

Experience building reusable AI frameworks, accelerators, and reference architectures.

Exposure to Model Risk Management, auditability, and compliance requirements in regulated industries.

Experience with AI evaluation frameworks such as Ragas, DeepEval, TruLens, or similar.

Knowledge of MLOps platforms and model lifecycle management tools.

Strong Prompt Engineering and Agent Optimization expertise.

Familiarity with Snowflake Cortex, Databricks, or modern AI and analytics platforms.

Experience mentoring junior developers and leading technical workstreams.

AWS AI/ML, Generative AI, or Cloud Technology certifications.