Software Engineer Python Advanced

Job Title: Software Engineer Python Advanced

Location: Columbus, OH

Duration: Long Term

Client: JPMC

We are looking for an Advanced Python Engineer / Agentic AI FDE with strong hands-on experience in Python development and a solid understanding of Generative AI, LLMs, AI Agents, and agentic application development .

The ideal candidate will work closely with client engineering and product teams to design, develop, integrate, and deploy production-grade agentic AI solutions . This role requires strong software engineering fundamentals, the ability to work with modern AI frameworks, and excellent client-facing problem-solving skills.

Key Competencies: Python | Agentic AI | Generative AI | LLMs | AI Agents | LangChain | LangGraph | OpenAI Agent SDK | RAG | Prompt Engineering | Vector Databases | FastAPI | REST APIs | AWS/Azure/GCP | Bedrock | Azure AI Foundry | Vertex AI | Docker | Kubernetes | CI/CD | AI Governance | Client Engineering | FDE

Key Responsibilities

• Design and develop scalable Agentic AI applications and AI-powered solutions using Python .

• Build, integrate, and optimize AI agents, multi-agent workflows, tools, and orchestration pipelines .

• Develop production-grade Python services, APIs, integrations, and backend components.

• Work with LLMs, prompt engineering, RAG, embeddings, vector databases, and tool/function calling .

• Implement agent workflows using frameworks such as LangChain, LangGraph, OpenAI Agent SDK, Google ADK, CrewAI, AutoGen, or similar frameworks .

• Integrate AI agents with enterprise systems, APIs, databases, SaaS platforms, and business applications.

• Develop and consume REST APIs, microservices, and event-driven integrations .

• Implement appropriate mechanisms for agent memory, context management, state management, and knowledge retrieval .

• Work with cloud-based AI platforms such as AWS Bedrock, Azure AI Foundry, or Google Cloud Vertex AI/Gemini .

• Implement observability, monitoring, logging, evaluation, and performance optimization for AI applications.

• Collaborate with architects, product managers, data scientists, and client stakeholders to translate business requirements into technical solutions.

• Participate in client discussions, technical workshops, solution demonstrations, and proof-of-concepts.

• Troubleshoot complex technical issues and provide hands-on engineering support during implementation.

• Follow secure and responsible AI engineering practices, including appropriate authentication, authorization, data protection, and AI governance .

Required Technical Skills

• Python Advanced

• Strong hands-on expertise in Python.

• Advanced knowledge of Python programming concepts, OOP, data structures, exception handling, concurrency/asynchronous programming, and performance optimization.

• Experience building production-grade applications and APIs using frameworks such as FastAPI, Flask, or Django .

• Strong understanding of testing, debugging, logging, packaging, and dependency management.

Agentic AI / Generative AI

• Strong understanding of LLMs, Generative AI, AI Agents, Agentic AI, and LLM application architecture .

• Hands-on experience with one or more agent frameworks such as:

  • LangChain / LangGraph

  • OpenAI Agent SDK

  • Google ADK

  • CrewAI

  • AutoGen

  • Microsoft Agent Framework or equivalent

• Experience with RAG, vector search, embeddings, prompt engineering, tool/function calling, structured outputs, and agent orchestration .

• Understanding of agent memory, context management, multi-agent systems, and agent evaluation.

Cloud & AI Platforms

• Experience with at least one major cloud platform: AWS, Azure, or GCP .

• Exposure to AI platforms such as Amazon Bedrock, Azure AI Foundry, Vertex AI/Gemini , or equivalent.

• Understanding of deploying AI applications in cloud environments.

APIs & Integration

• Strong experience with REST APIs, JSON, web services, authentication, and third-party integrations.

• Experience integrating AI solutions with enterprise applications and data sources.

• Understanding of microservices and distributed application architecture.

Data & Databases

• Experience with SQL and relational databases.

• Exposure to NoSQL databases and vector databases such as Pinecone, Weaviate, Milvus, pgvector, or equivalent .

• Understanding of data ingestion, retrieval, chunking, embeddings, and knowledge bases.

Preferred Skills

• Experience with Docker, Kubernetes, CI/CD, Git, and cloud deployment .

• Exposure to AI observability and evaluation tools.

• Understanding of AI governance, guardrails, responsible AI, and security considerations for agentic systems .

• Experience with MCP (Model Context Protocol) and enterprise tool integrations.

• Experience working with enterprise-grade AI platforms or agent orchestration platforms.

• Knowledge of authentication and authorization mechanisms such as Oauth2/JWT.

• Experience working in financial services, banking, or other highly regulated environments is a plus.

FDE / Client-Facing Skills

• Strong communication and stakeholder management skills.

• Ability to work directly with client engineering, architecture, and product teams.

• Ability to understand ambiguous business problems and convert them into technical solutions.

• Comfortable conducting technical workshops, architecture discussions, POCs, demos, and troubleshooting sessions .

• Ability to work independently in a fast-paced client environment.

• Strong analytical and problem-solving skills.

Education & Experience

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical discipline.

• 5+ years of software engineering experience , with strong hands-on Python development experience.

• 2+ years of experience in Generative AI / LLM / Agentic AI development preferred.

• Proven experience delivering production-grade applications or AI solutions.