AI Lead Developer - Agentic AI & GenAI

SID Global Solutions
Exton, United States of America
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Remote
Exton, United States of America

Tech stack

Artificial Intelligence
Amazon Web Services (AWS)
Azure
Cloud Computing
Cloud Engineering
Code Review
Continuous Integration
Distributed Systems
Memory Management
Python
Redis
Search Technologies
Software Engineering
Google Cloud Platform
Flask
Multi-Agent Systems
Prompt Engineering
Spark
IT Architecture
Generative AI
FastAPI
Kubernetes
HuggingFace
Kafka
Machine Learning Operations
Virtual Agents
REST
Docker
Microservices

Job description

  • Design and develop enterprise-grade Agentic AI and Generative AI solutions.
  • Build multi-agent systems using LangGraph, AutoGen, ADK, MCP, and related frameworks.
  • Develop RAG-based applications leveraging vector databases and enterprise knowledge sources.
  • Build scalable APIs and AI microservices using Python, FastAPI, and cloud-native architectures.
  • Deploy AI solutions on AWS, Azure, or Google Cloud Platform using Docker, Kubernetes, and CI/CD pipelines.
  • Implement AI security, governance, observability, and guardrails.
  • Collaborate with business, product, and engineering teams to deliver AI-driven solutions.
  • Conduct code reviews, mentor engineers, and contribute to AI architecture and roadmap planning.

Requirements

  • 10+ years of software engineering experience with 4+ years in AI/GenAI solutions.

  • Strong Python development experience with FastAPI or Flask.

  • Hands-on experience with:

  • LangChain

  • LangGraph

  • AutoGen

  • ADK

  • MCP (Model Context Protocol)

  • Multi-Agent Architectures

Experience building RAG pipelines, embeddings, prompt engineering, and vector search solutions.

Experience with vector databases such as Pinecone, Weaviate, FAISS, Chroma, or Azure AI Search.

Strong knowledge of REST APIs, microservices, distributed systems, and cloud platforms (AWS/Azure/Google Cloud Platform).

Experience with Docker, Kubernetes, Redis, Kafka, and AI application deployment.

Strong understanding of AI security, memory management, scalability, and production AI systems.

Preferred Skills

  • Experience with OpenAI, Azure OpenAI, Claude, Gemini, and Hugging Face models.
  • Knowledge of MLOps, AI evaluation frameworks, and AI governance.
  • Experience with Spark, Kafka, and large-scale AI platforms.
  • Prior experience leading AI initiatives and mentoring engineering teams.

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