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FocalWorks - AI Engineer - Python

Focalworks Solutions
2 - 4 Years
Multiple Locations

Posted on: 11/09/2026

Job Description

The Role :

We are looking for an AI Engineer / Generative AI Developer with good Python fundamentals and hands-on exposure to Large Language Models and modern AI development tools.

You will work with experienced developers and product teams to build AI-powered applications such as intelligent assistants, knowledge systems, workflow automation, data extraction tools, and AI agents.

This role is ideal for someone who has already experimented with Generative AI through projects or professional work and now wants to develop deeper practical experience building production-ready applications.

Key Responsibilities :

- Build Generative AI Applications: Develop applications using leading Large Language Models through APIs and existing AI platforms.

- Build AI Assistants and Simple Agents: Create conversational assistants and agentic workflows that can retrieve information, use tools, call APIs, and perform multi-step tasks.

- Implement RAG Systems: Build Retrieval-Augmented Generation solutions using documents, databases, embeddings, and vector search.

- Integrate APIs and Tools: Connect AI applications with external APIs, databases, business systems, and other software services.

- Prompt and Context Engineering: Design and improve prompts, system instructions, examples, retrieved context, and conversation history to improve the reliability of AI applications.

- Work with Structured and Unstructured Data: Prepare and transform data from documents, APIs, databases, spreadsheets, and other sources for use in AI applications.

- Build and Integrate APIs: Develop REST APIs and backend services that expose AI functionality to web and mobile applications.

- Test AI Outputs: Help create test cases and simple evaluation methods to measure the accuracy, relevance, and reliability of AI responses.

- Improve Reliability: Implement practical validation, error handling, retries, permissions, and guardrails around AI workflows.

- Deploy AI Applications: Assist with deploying and maintaining AI services in development and production environments.

- Learn Continuously: Keep up with developments in Generative AI and experiment with new models, frameworks, and techniques where they can improve our applications.

Required Qualifications :

Software Development Fundamentals :

- Good proficiency in Python.

- Understanding of software development fundamentals and clean coding practices.

- Experience working with REST APIs and JSON.

- Familiarity with databases such as PostgreSQL, MySQL, MongoDB, or similar.

- Comfortable working with Git and standard development workflows.

Generative AI Fundamentals:

- Hands-on experience using Large Language Models such as OpenAI, Anthropic, Gemini, or open-source models.

- Understanding of how LLMs work at a practical level, including their capabilities and limitations.

- Experience writing and improving prompts for LLM applications.

- Basic understanding of embeddings, semantic search, vector databases, and RAG.

- Some experience building applications using an LLM framework such as LangChain, LlamaIndex, or similar.

- Understanding of tool/function calling and how an AI application can interact with external systems.

- Familiarity with managing conversation history and context within LLM applications.

Data and AI Knowledge:

- Comfortable working with structured and unstructured data.

- Basic familiarity with machine learning concepts.

- Exposure to libraries such as Pandas and NumPy.

- Familiarity with Hugging Face or open-source AI models is useful but not mandatory.

Nice to Have:

- Experience deploying an AI application to the cloud.

- Experience with vector databases such as Pinecone, Qdrant, Weaviate, Chroma, or pgvector.

- Experience building AI agents or multi-step workflows.

- Familiarity with Docker.

- Experience working with document extraction, OCR, image understanding, or multimodal AI.

- Understanding of MCP or similar approaches for connecting AI systems with tools.

- Personal AI projects, GitHub repositories, hackathon projects, or experimentation with new AI tools.

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