Senior AI/ML Engineer

TEKsystems•Austin, TX

1d•$119,800 - $179,800•Remote

About The Position

Think of TEKsystems Global Services (TGS) as the growth solution for enterprises today. We unleash growth through technology, strategy, design, execution and operations with a customer-first mindset for bold business leaders. We deliver cloud, data and customer experience solutions. Our partnerships with leading cloud, design and business intelligence platforms fuel our expertise. We value deep relationships, dedication to serving others and inclusion. We drive positive outcomes for our people and our business, and we stay true to our commitments and act in harmony with our words. We exist to create significant opportunity for people to achieve fulfillment through career success. Ready to join us? Here’s what the opportunity supported through our TGS Talent Acquisition Team requires: We are seeking a highly skilled and experienced Senior Full Stack AI/ML Engineer with Product and AI First Mindset to join our team. This role involves designing and developing cutting-edge AI solutions, including agentic AI systems, multi-agent orchestration, and contributing to the full software development lifecycle from frontend to backend. You'll work on building world class AI Products on latest AI frameworks, large language models, and modern DevOps practices to build scalable, production-ready AI applications.

Requirements

5+ years of experience in full stack development with proficiency in modern frameworks and programming languages
3+ years of hands on experience building AI powered applications and autonomous agent systems
Programming Languages: Proficiency in Python and TypeScript/JavaScript; experience with Rust, Go, or Java a plus
Frontend Frameworks: Experience with React, Vue.js, Angular, Next.js, or similar modern frontend frameworks
Backend Technologies: Node.js, FastAPI, Django, Express.js, and microservices-based architectures
Agent Frameworks: Hands on experience with LangChain, AutoGen, CrewAI, LangGraph, OpenAI Assistants API, or Microsoft ADK
LLM Integration: Proven experience integrating and optimizing models such as GPT, Claude, Gemini, and open source LLMs (Llama 3, Mistral, CodeLlama, Vicuna)
AI/ML Fundamentals: Strong understanding of transformer architectures, prompt engineering, embeddings, vector databases, and RAG systems
Proven experience building autonomous agents, multi agent systems, and agent orchestration platforms
Deep understanding of agent based modeling, reinforcement learning, AI planning methods, and decision making algorithms
Experience working with Model Context Protocol (MCP) and multi model integration workflows
Knowledge of AI safety, alignment, and responsible deployment methodologies
Familiarity with vector databases like Pinecone, Weaviate, and Chroma, and experience implementing semantic search

Nice To Haves

Experience using LangFuse for AI observability, tracing, and performance monitoring
Knowledge of AWS Strands or similar agent coordination platforms
Experience deploying or fine tuning open source LLMs using tools such as Hugging Face, Ollama, or vLLM
Familiarity with AI development tools: Cursor, GitHub Copilot, Claude Code, Gemini CLI
Understanding of RAG, knowledge graph architectures, and semantic search techniques
Experience with MLOps practices including model versioning, experiment tracking, and automated deployment pipelines
Knowledge of Kubernetes for AI workload orchestration, distributed systems, and GPU cluster management
Familiarity with cloud AI services like AWS Bedrock, Google Vertex AI, Azure OpenAI
Experience with AI specific monitoring and logging solutions
Background in Full Stack Product development and deployed in enterprise or consumer marketplace
Understanding of Product Engineering, conversational AI, task automation, or decision support systems
Experience with AI governance, model evaluation methodologies, and safety testing frameworks
Strong proficiency in NLP, language models, prompt engineering, and context engineering

Responsibilities

Design and implement scalable full stack applications/products integrating advanced AI capabilities and autonomous agent systems.
Develop and maintain sophisticated agentic AI Products and Solutions, including autonomous agents, multi agent systems, and AI orchestration workflows.
Build intelligent agents capable of reasoning, planning, decision making, and autonomous task execution.
Implement agent communication protocols and coordination mechanisms for complex multi agent scenarios.
Design and optimize AI workflows using agent frameworks such as Google ADK, A2A, AutoGen, CrewAI, LangGraph, LangFlow, Semantic Kernel, and OpenAI Agent SDK.
Architect and develop enterprise products leveraging robust frontend interfaces and backend services for AI driven platforms using modern frameworks.
Integrate multiple Large Language Models (LLMs), including Open AI, Anthropic, Google and other open source models like Llama 3, Mistral, CodeLlama,
Implement and optimize AI orchestration frameworks including LangChain and LlamaIndex.
Design Model Context Protocol (MCP) implementations for seamless model interoperability.
Develop custom agent frameworks and extend existing platforms like Microsoft AI Agent Development Kit (ADK) and Google AI Platform.
Implement comprehensive AI observability and monitoring using tools such as LangFuse, Phoenix, Datadog, or Dynatrace.
Deploy and manage AI applications using containerization (Docker, Kubernetes) and cloud platforms (AWS, GCP, Azure).
Establish CI/CD pipelines for AI model deployment, version control, and automated testing.
Implement prompt engineering best practices, A/B testing frameworks for AI responses, and performance optimization.
Monitor model performance, detect drift, and implement feedback loops for continuous improvement.
Collaborate with research, product, and data science teams to prototype and deploy production ready intelligent systems.
Ensure scalability, reliability, security, and ethical considerations in the deployment of agentic AI systems.
Participate in code reviews, testing, documentation, and knowledge sharing to ensure high quality software delivery.
Mentor junior developers and contribute to technical decision making processes.