Python Developer – AI Engineering

Teamware Solutions is seeking a Python Developer for AI Engineering and Generative AI work. The role focuses on building Python backend services and APIs, developing LLM and RAG workflows, integrating GCP services, and supporting testing, deployment, and collaboration across teams.

Responsibilities

Design, develop, and maintain Python-based backend services and APIs for AI-enabled applications, with strong emphasis on clean, modular, production-ready code

Build and integrate Generative AI workflows using LLMs, RAG pipelines, prompt orchestration, and structured-output processing

Develop FastAPI-based REST endpoints to support file processing, pipeline execution, asynchronous workflows, and integration with external enterprise applications

Implement retrieval workflows using GCP services such as Vertex AI, Vertex AI Search, Cloud Storage, BigQuery, Pub/Sub, Secret Manager, and Cloud Run

Develop data-processing logic for structured and unstructured inputs, including document parsing, metadata generation, validation, transformation, and downstream persistence

Support integration testing, debugging, deployment, logging, monitoring, and troubleshooting of AI applications across development and QA environments

Collaborate with solution architects, cloud infrastructure teams, product owners, and business stakeholders to translate requirements into working AI features and scalable backend components

Contribute to prompt engineering, output validation, error handling, retry logic, and guardrails to improve reliability of AI pipeline responses

Maintain technical documentation, API contracts, configuration files, deployment artifacts, and reusable engineering components

Preferred

Experience with Agentic AI frameworks or multi-step AI orchestration

Familiarity with Vertex AI Vector Search, Graph RAG, or knowledge graph concepts

Experience with Pub/Sub-based asynchronous processing and event-driven architectures

Understanding of OAuth, service-to-service authentication, IAM, signed URLs, and secure API integration

Exposure to React or frontend integration is useful but not mandatory

Familiarity with AI evaluation metrics such as groundedness, relevance, completeness, coherence, and confidence scoring

Healthcare-domain exposure is beneficial, especially where the solution involves enterprise workflow, requirements, or document intelligence

Agentic AI frameworks

Multi-step AI orchestration

Vertex AI Vector Search

Graph RAG

Knowledge graphs

Pub/Sub processing

Event-driven architectures

OAuth

Service-to-service authentication

Access Management

Signed URLs

Secure API integration

React

Frontend integration

AI evaluation metrics

Groundedness evaluation

Relevance evaluation

Completeness evaluation

Coherence evaluation

Confidence scoring

Healthcare domain knowledge

Enterprise workflows

Requirements analysis

Document intelligence

Benefits

100% Remote

Company

Staff augmentation and professional consulting services

Chennai, Tamil Nadu, IND

http://www.teamwaresolutions.net/

Founded in 2003

1001-5000 employees

Qualifications

4–7 years of software development experience, with strong hands-on experience in Python backend development

At least 1–2 years of practical experience with Generative AI, LLM-based applications, or RAG solutions

Experience building REST APIs using FastAPI, Flask, or similar Python frameworks, preferably FastAPI

Hands-on experience working with Google Cloud Platform, especially Cloud Run, Cloud Storage, Vertex AI, BigQuery, Pub/Sub, IAM, and Secret Manager

Experience integrating AI/ML services into enterprise applications using APIs, authentication, asynchronous processing, and cloud-native services

Experience processing structured and unstructured data formats such as JSON, JSONL, Excel, CSV, PDF, Word documents, and text

Experience with source control, CI/CD, containerization, and deployment workflows using Git, Docker, GitLab/GitHub, and cloud deployment pipelines

Exposure to debugging distributed or cloud-hosted applications using logs, monitoring, request tracing, and error analysis

Experience working in Agile delivery teams and collaborating with cross-functional stakeholders

Python – strong programming fundamentals, object-oriented design, modular coding, exception handling, testing, and package management

Generative AI / LLMs – prompt engineering, structured outputs, model invocation, response validation, token usage, and basic evaluation concepts

RAG – document ingestion, chunking, embeddings, vector retrieval, metadata filtering, reranking, and grounding

GCP – practical experience with Vertex AI, Vertex AI Search, Cloud Run, GCS, BigQuery, Pub/Sub, Secret Manager, IAM, and Cloud Logging

FastAPI / REST APIs – endpoint development, request/response models, authentication, async processing, status handling, and API integration

Data Processing – pandas, openpyxl, JSON/JSONL handling, document processing, validation, and transformation

Cloud-Native Development – Docker, service accounts, environment variables, secrets, CI/CD, deployment, and runtime troubleshooting

Git – branching, pull requests, merge conflict resolution, version control, and collaborative development

Testing & Debugging – unit testing, API testing, integration testing, Postman/cURL, log analysis, and production issue troubleshooting

Experience with Agentic AI frameworks or multi-step AI orchestration

Familiarity with Vertex AI Vector Search, Graph RAG, or knowledge graph concepts

Experience with Pub/Sub-based asynchronous processing and event-driven architectures

Understanding of OAuth, service-to-service authentication, IAM, signed URLs, and secure API integration

Exposure to React or frontend integration is useful but not mandatory

Familiarity with AI evaluation metrics such as groundedness, relevance, completeness, coherence, and confidence scoring

Healthcare-domain exposure is beneficial, especially where the solution involves enterprise workflow, requirements, or document intelligence

4–7 years of software development experience, with strong hands-on experience in Python backend development.

At least 1–2 years of practical experience with Generative AI, LLM-based applications, or RAG solutions.

Required skills

Python, Generative AI and LLMs, Retrieval-Augmented Generation (RAG), Google Cloud Platform (GCP), Vertex AI Search, FastAPI, REST API Development, pandas and openpyxl, Docker, Git, CI/CD, Unit and Integration Testing

Experience

4-7 years