Forward Deployed Engineer

About the role

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