Ex-JPMC AI/ML Engineer

Synapse Tech Services Inc; Plano (TX); On-site; USD 130,000 - 180,000; Full time

Job summary

Synapse Tech Services Inc. seeks a Senior AI/ML Full Stack Engineer to design and deploy production-grade AI applications using Java or Python, with 7–10+ years of full-stack experience and hands-on agentic AI development.

You will implement RAG pipelines, manage vector stores, and orchestrate AI agents in fast-paced, in-office environments. Responsibilities include building end-to-end AI solutions, deploying via AWS Bedrock and Claude APIs, and ensuring responsible AI practices with guardrails

Qualifications

• 10+ years software development experience in Java or Python, OR 7+ years if entirely full-stack + Agentic AI development experience.
• 2+ years hands-on experience building AI/ML applications in production
• Strong proficiency with RAG architectures — chunking strategies, embedding models, vector stores like Pinecone, OpenSearch, pgvector, FAISS
• Experience with AI orchestration frameworks: LangChain, LlamaIndex, Semantic Kernel, or CrewAI
• Hands-on experience with AWS Bedrock, Anthropic Claude models, and model invocation APIs
• Proven prompt engineering skills — system prompts, few-shot, chain-of-thought, tool use, structured outputs
• Experience building conversational AI: chatbots (text) and voicebots (speech-to-text, text-to-speech)
• Proficiency with AWS services (Lambda, Step Functions, API Gateway, S3, DynamoDB, SQS)
• Experience with CI/CD pipelines, containerization (Docker, ECS/EKS), and infrastructure-as-code
• Strong understanding of API design (REST, GraphQL), microservices architecture, and event-driven systems
• Familiarity with evaluation frameworks for LLM outputs
• Experience with guardrails, content filtering, and responsible AI practices

Responsibilities

• Design and build AI/ML applications end-to-end, from architecture through production deployment
• Implement RAG pipelines, including chunking strategies, embedding models, and vector store integration (Pinecone, OpenSearch, pgvector, FAISS)
• Build and orchestrate AI agents using frameworks such as LangChain, LlamaIndex, Semantic Kernel, or CrewAI
• Develop and deploy solutions using AWS Bedrock, Anthropic Claude models, and model invocation APIs
• Apply advanced prompt engineering techniques — system prompts, few-shot, chain-of-thought, tool use, structured outputs
• Build conversational AI experiences, including chatbots (text) and voicebots (speech-to-text, text-to-speech)
• Design and maintain APIs (REST, GraphQL), microservices, and event-driven architectures
• Own CI/CD pipelines, containerization (Docker, ECS/EKS), and infrastructure-as-code for production systems
• Implement evaluation frameworks, guardrails, content filtering, and responsible AI practices across LLM-powered features

Skills

Full stack development

Agentic AI development

RAG architectures

Prompt engineering

API design

CI/CD pipelines

AWS deployment

Education

Bachelor's degree

Tools

LangChain

LlamaIndex

Semantic Kernel

CrewAI

Pinecone

OpenSearch

pgvector

FAISS

Docker

ECS/EKS

AWS Bedrock

Anthropic Claude

Job description

Who You Are

You are a Senior AI/ML Full Stack Engineer who brings deep hands-on experience building production-grade AI applications with Java or Python. You''ve spent 7-10+ years mastering full-stack development and have moved confidently into agentic AI, RAG architectures, and LLM orchestration. You''re just as comfortable designing a vector store retrieval pipeline as you are hardening a CI/CD deployment on AWS. You thrive in fast-paced, in-office environments where live coding and hands-on problem solving are part of the culture, and you''re excited to bring responsible AI practices — guardrails, evaluation frameworks, and content filtering — into everything you build.

What You''ll Do

• Design and build AI/ML applications end-to-end, from architecture through production deployment
• Implement RAG pipelines, including chunking strategies, embedding models, and vector store integration (Pinecone, OpenSearch, pgvector, FAISS)
• Build and orchestrate AI agents using frameworks such as LangChain, LlamaIndex, Semantic Kernel, or CrewAI
• Develop and deploy solutions using AWS Bedrock, Anthropic Claude models, and model invocation APIs
• Apply advanced prompt engineering techniques — system prompts, few-shot, chain-of-thought, tool use, structured outputs
• Build conversational AI experiences, including chatbots (text) and voicebots (speech-to-text, text-to-speech)
• Design and maintain APIs (REST, GraphQL), microservices, and event-driven architectures
• Own CI/CD pipelines, containerization (Docker, ECS/EKS), and infrastructure-as-code for production systems
• Implement evaluation frameworks, guardrails, content filtering, and responsible AI practices across LLM-powered features

What You Bring

• Bachelor''s degree required
• 10+ years of software development experience (Java or Python), OR 7+ years if entirely full-stack + Agentic AI development experience
• 2+ years hands-on experience building AI/ML applications in production
• Strong proficiency with RAG architectures — chunking strategies, embedding models, vector stores (Pinecone, OpenSearch, pgvector, FAISS)
• Experience with AI orchestration frameworks: LangChain, LlamaIndex, Semantic Kernel, or CrewAI
• Hands-on experience with AWS Bedrock, Anthropic Claude models, and model invocation APIs
• Proven prompt engineering skills — system prompts, few-shot, chain-of-thought, tool use, structured outputs
• Experience building conversational AI: chatbots (text) and voicebots (speech-to-text, text-to-speech)
• Proficiency with AWS services (Lambda, Step Functions, API Gateway, S3, DynamoDB, SQS)
• Experience with CI/CD pipelines, containerization (Docker, ECS/EKS), and infrastructure-as-code
• Strong understanding of API design (REST, GraphQL), microservices architecture, and event-driven systems
• Familiarity with evaluation frameworks for LLM outputs
• Experience with guardrails, content filtering, and responsible AIt practices