AI/ML Engineer Python, LangChain & Google ADK
Why This Role Stands Out
Advance your career as an AI/ML Engineer by building cutting-edge Generative AI applications and intelligent agents using Python, LangChain, and Google ADK, with the flexibility of a hybrid work model. This role is perfect for experienced engineers passionate about LLMs and RAG architectures, offering significant opportunities to shape innovative AI solutions. You are encouraged to apply and contribute to impactful projects in this dynamic field.
Quick Overview
Job Description
Role: AI/ML Engineer Python, LangChain & Google ADK
Location: Dallas, TX
Duration: 12 Months Contract
Job Summary:
- We are seeking an experienced AI/ML Engineer with expertise in Python, LangChain, and Google Agent Development Kit (Google ADK) to build and deploy enterprise-grade Generative AI applications and intelligent AI agents. The ideal candidate will have strong experience with LLMs, RAG architectures, prompt engineering, and cloud-native AI solutions.
Required Skills:
- 8+ years of software development experience with strong Python expertise
- Hands-on experience with LangChain and Google ADK (Agent Development Kit)
- Experience building AI agents using LLMs such as Gemini, OpenAI, Claude, or Llama
- Strong understanding of Retrieval-Augmented Generation (RAG), prompt engineering, and vector databases
- Experience with Google Cloud Platform (Google Cloud Platform), especially Vertex AI and Gemini APIs
- Knowledge of REST APIs, microservices, and Docker
- Experience with Git, CI/CD, and Agile development
- Familiarity with SQL/NoSQL databases
Preferred Skills:
- Experience with LangGraph, CrewAI, AutoGen, or similar agentic AI frameworks
- Knowledge of Pinecone, Weaviate, ChromaDB, or FAISS
- Experience deploying AI applications on Kubernetes or Google Cloud Platform
Responsibilities:
- Design and develop AI-powered applications and intelligent agents
- Build RAG pipelines and integrate LLMs using LangChain and Google ADK
- Develop scalable APIs and backend services in Python
- Optimize AI model performance, accuracy, and latency
- Collaborate with cross-functional teams to deliver production-ready AI solutions
- Follow best practices for testing, deployment, monitoring, and MLOps
Regards,
Vasu Nag
Associate- Talent Acquisition
Email:
Skills
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