The Role
Develop modular Python systems for AI-driven code modernization using LangChain, LangGraph, LLMs, workflow orchestration, and state management. Build RAG pipelines, vector searches, dependency matrices, database persistence, and code analysis workflows. Integrate multiple LLM providers, create robust tooling, and maintain tests, logging, and error handling. Collaborate with client engineering teams, participate in SAFe Agile ceremonies, and document work in JIRA.
Summary Generated by Built In
Senior AI Engineer
Pune, India
About Us
Coditation was founded by a serial entrepreneur, and a team of young talented technologists with a vision of delivering high-quality, scalable, and best-in-class products at the bleeding edge of technology . We specialize in Machine Learning & AI, Data Engineering, Cloud, and Enterprise Mobility. We have built a team of ninja architects, data scientists, data engineers, and software engineers having decades of collective experience of applying emerging technologies to build cutting edge software products, and are constantly looking to add high-quality and passionate engineers.
What we are looking for
We are Seeking a Senior AI Engineer to serve as an embedded technical expert within a client’s engineering team. You will be a key member of the team developing and optimizing advanced, AI-driven solutions for a code modernization platform. This role requires a blend of critical thinking and hands-on development skills to build modular Python systems that leverage state management, workflow orchestration, and large language models (LLMs) to modernize complex software systems.
What would your day look like?
● Agentic & Workflow Engineering: Design and implement modular Python systems using LangGraph and LangChain to manage state, configuration, and complex workflow orchestration.
● Code Modernization: Design AI workflows for reverse and forward engineering, including code analysis, summarization, and dependency transformation.
● RAG & Vector Operations: Build and maintain high-performance Retrieval-Augmented Generation (RAG) pipelines and database operations for storing dependency matrices and workflow results.
● Multi-LLM Integration: Integrate and optimize various LLMs (e.g., Gemini, Claude, GPT-4, Vertex AI) for code analysis and automated generation.
● Database Management: Manage data persistence using PostgreSQL with the pgvector extension, including schema management and efficient similarity searches.
● Robust Tooling: Develop utilities for file handling, model operations, and ensuring robust logging and error handling across applications. What you will need
● Collaboration: Work as a seamless member of the client’s team, collaborating with leads and architects to define requirements and deliver scalable AI solutions.
● Quality Standards: Write and maintain comprehensive unit and integration tests for all major components while adhering to Pythonic best practices.
● Agile Governance: Participate in SAFe Agile ceremonies and maintain meticulous project tracking and documentation in JIRA for internal and external stakeholders.
Technical Skills:
● Core AI Frameworks: Expert proficiency in LangChain, LangGraph, and agentic AI development; deep understanding of tokenization and prompt engineering.
● Programming & Patterns: 5+ years of professional Python development with deep knowledge of packages like PyYAML, python-dotenv, SQLAlchemy, and psycopg2.
● Data & Vector Search: Strong background in SQL/NoSQL, specifically PostgreSQL and vector embedding concepts.
● Modern Dev Stack: Expert use of VS Code, Git for version control, and YAML/JSON for configuration management.
Preferred Pluses:
● Experience with Knowledge Graphs.
● Familiarity with Java and React tech stacks for cross-language workflows.
● Prior experience in insurance, finance, or regulated enterprise environments.
Skills Required
- 5+ years of professional Python development
- Expert proficiency in LangChain and LangGraph
- Experience with agentic AI development, tokenization, and prompt engineering
- Knowledge of PyYAML, python-dotenv, SQLAlchemy, and psycopg2
- Strong SQL/NoSQL background, including PostgreSQL and vector embeddings
- Expertise with VS Code, Git, and YAML/JSON configuration management
- Experience writing unit and integration tests
- Experience with knowledge graphs
- Familiarity with Java and React technology stacks
- Experience in insurance, finance, or regulated enterprise environments
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The Company
What We Do
is a boutique technology services and solutions firm specializing in Machine Learning & AI, Data Engineering, and Cloud. It has a team of ninja architects, data scientists, data engineers, and software engineers having a decades of collective experience of applying emerging technologies to build cutting edge software products
