Forward Deployed Engineer

Overview:

• We are seeking a Forward Deployed Engineer to join a client-facing forward deployment engineering team. This individual will partner with business and technical stakeholders to analyze existing workflows, identify opportunities for AI-enabled automation, and implement reliable solutions that improve efficiency, decision support, and user experience.
• The ideal candidate is a hands-on AI engineer with a software development or data engineering background who can translate loosely defined business problems into production-ready technical solutions. This role requires strong communication, problem-solving, integration, and operational troubleshooting skills.
• This is a six-month contract-to-hire opportunity based in Frisco, Texas, with three days per week onsite.

Requirements

• Experience discovering, analyzing, and implementing AI-enabled workflows
• Hands-on experience with generative AI, LLM applications, RAG, AI agents, or intelligent automation
• Experience designing agentic workflows involving orchestration, tool calling, APIs, state, memory, or human review
• Proficiency in at least one programming language such as Python, Java, TypeScript, JavaScript, or C#
• Experience building APIs, backend services, data pipelines, microservices, or system integrations
• Experience with an AI platform or framework such as Azure OpenAI, AWS Bedrock, OpenAI, LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or a comparable technology
• Experience with AWS, Azure, GCP, or another enterprise cloud platform
• Ability to translate business scenarios into technical requirements, implementation tasks, and acceptance criteria
• Strong operational troubleshooting and root-cause analysis skills
• Experience validating AI outputs, integrations, and workflow behavior
• Understanding of data movement, system dependencies, exception handling, and production support
• Experience participating in Agile delivery, including sprint planning, backlog refinement, testing, and release readiness
• Strong communication skills with the ability to work directly with clients and cross-functional stakeholders

Responsibilities

• Conduct discovery sessions with business and technical stakeholders to understand current workflows, pain points, decisions, exceptions, and desired outcomes
• Map business processes and data flows across applications, APIs, databases, users, and external systems
• Identify appropriate opportunities for AI assistance, deterministic automation, and human approval
• Design and implement AI-enabled automation patterns using LLMs, RAG, agents, tools, integrations, and business logic
• Configure AI agents, prompts, retrieval components, workflow state, tool permissions, and orchestration logic
• Develop APIs, services, integration components, and data-processing logic that connect AI solutions with enterprise systems
• Establish human-in-the-loop controls, validation rules, escalation paths, and safe automation boundaries
• Test normal scenarios, edge cases, failures, and integration behavior before production deployment
• Define evaluation criteria for accuracy, relevance, groundedness, reliability, latency, and operational performance
• Troubleshoot application, model, retrieval, data, integration, and performance issues
• Implement logging, monitoring, observability, error handling, rollback, and production-support procedures
• Translate business requirements into technical stories, implementation plans, acceptance criteria, and documentation
• Participate in Agile ceremonies and collaborate with engineering, product, data, operations, security, and business teams
• Demonstrate solutions to stakeholders, incorporate feedback, and support adoption from prototype through production
• Document workflow designs, architecture decisions, configurations, operating procedures, and lessons learned