Sr AI/ML Engineer with Python + AWS

Job Title: Sr AI/ML Engineer with Python + AWS

Location: Plano, TX (Onsite)

Duration: 6-month contract-to-hire

2 rounds of interviews (final round onsite) + Coding session

Job Responsibilities

• Looking for a very strong Python developer with a focus on AI/ML Applications AI/ML is the primary with Python as the coding side
• Must be very strong in RAG architecture as well as deployments - chunking strategies, embedding models, vector stores (Pinecone, OpenSearch, pgvector, FAISS)
• Must be very strong in AWS services (Lambda, Step Functions, API Gateway, S3, DynamoDB, SQS)
• Must have experience with AI orchestration frameworks: LangChain, LlamaIndex, Semantic Kernel, or CrewAI
• Understanding of chat bots (speech to text, text to speech)
• Strong understanding of API design (REST, GraphQL), microservices architecture, and event-driven systems
• Must have Hands-on experience with AWS Bedrock, Anthropic Claude models, and model invocation APIs
• Familiarity with evaluation frameworks for LLM outputs
• Should have experience with guardrails, content filtering, and responsible AI practices

MUST Have skills

• java or python
• proficient with AI_ML architecture - hands on work in production
• CICD pipeline
• API building
• 10+ years of software development experience (Java or Python)
• 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 integration)
• 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