Posted:1 week ago|
Platform:
On-site
Contractual
Our Client is a global IT services company headquartered in Southborough, Massachusetts, USA. Founded in 1996, with a revenue of $1.8B, with 35,000+ associates worldwide, specializes in digital engineering, and IT services company helping clients modernize their technology infrastructure, adopt cloud and AI solutions, and accelerate innovation. It partners with major firms in banking, healthcare, telecom, and media.
Our Client is known for combining deep industry expertise with agile development practices, enabling scalable and cost-effective digital transformation. The company operates in over 50 locations across more than 25 countries, has delivery centers in Asia, Europe, and North America and is backed by Baring Private Equity Asia.
Develop and deploy AI features and automation workflows using Python, integrating LLMs and Agentic frameworks for scalable and intelligent applications.
Technical Responsibilities:
Build Python-based microservices and APIs integrating LLMs via SDKs or REST APIs (OpenAI, Anthropic, Bedrock, Azure OpenAI).
Develop agentic workflows using frameworks like CrewAI, AutoGen, LangGraph, or Semantic Kernel.
Implement RAG systems combining embedding models, vector databases, and LLM reasoning components.
Create prompt templates, tool use logic, and memory management layers for multi-step AI reasoning.
Integrate data sources (files, APIs, databases) with embedding pipelines using FAISS, Chroma, or Pinecone.
Write custom Python utilities for evaluation, testing, and logging of model outputs and agent responses.
Develop asynchronous and event-driven backend components with FastAPI or Flask.
Implement unit/integration tests for AI pipelines using pytest and unittest.
Use Docker and Kubernetes for containerized deployment and scaling of AI workloads.
Contribute to observability and logging using Prometheus, Grafana, or OpenTelemetry.
Optimize prompt and inference latency through caching, batching, and lightweight model selection.
Technical Stack:
Languages: Python 3.10+, TypeScript (optional)
Frameworks: FastAPI, LangChain, LlamaIndex, CrewAI, AutoGen
AI/ML: Hugging Face Transformers, PyTorch, OpenAI SDK, Anthropic API
Databases: Chroma, Pinecone, PostgreSQL, Redis
Tools: Docker, Git, pytest, MLflow, Ray, VS Code
Cloud: AWS Bedrock, Azure OpenAI, GCP Vertex AI
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