Forward Deployed Engineer
DataArt
Project overview
You will be involved in an enterprise AI initiative focused on transforming business workflows into production-ready AI agent capabilities. The project aims to create governed, scalable, and reusable agent solutions that improve efficiency, decision-making, and knowledge work across the organization.
Team
You will work within a cross-functional delivery team that includes AI specialists, software engineers, architects, QA engineers, DevOps, and business stakeholders. The team operates in a collaborative and iterative delivery model, emphasizing experimentation, validation, and responsible deployment of AI solutions.
Position overview
We are looking for a Forward Deployed Engineer who will work at the intersection of business and engineering to design, build, and implement AI-powered agent solutions. You will collaborate closely with business stakeholders and technical teams to translate real workflows into structured, working, and production-ready capabilities. This role combines hands-on engineering with business understanding, enabling you to contribute to impactful AI-driven solutions.
Technology stack
AI agent platforms, AgentCore, Claude, Microsoft Copilot, cloud platforms, APIs, data pipelines, workflow automation tools, frontend and backend technologies, observability and monitoring tools, testing frameworks, DevOps practices
Responsibilities
Work with business stakeholders to understand existing workflows and operational challenges
Identify opportunities where AI agents can improve efficiency, quality, and decision-making
Translate business needs into structured requirements, technical designs, and implementation steps
Build and configure AI agent prototypes using approved tools and platforms
Validate solutions with end users and iterate based on feedback
Collaborate with engineering, architecture, security, QA, and AI teams to ensure responsible solution design
Define agent behavior, including data access, tool integration, and human review points
Support testing and evaluation of agent outputs for quality, accuracy, and reliability
Prepare release documentation, including known limitations, user guidance, and operational procedures
Monitor adoption, user feedback, and performance after deployment
Capture reusable patterns, workflows, prompts, and implementation approaches for future use
Requirements
Hands-on experience in software engineering and application development
Experience working with APIs, integrations, and cloud-based systems
Ability to work across frontend, backend, data, and deployment layers
Practical exposure to AI tools, large language models, or workflow automation solutions
Experience translating business workflows into technical implementations
Strong problem-solving skills in environments with evolving requirements
Ability to communicate effectively with both technical and non-technical stakeholders
Experience documenting requirements, design decisions, and implementation details
Understanding of secure development practices, data access control, and testing approaches
Experience working within structured delivery models and producing clear handover materials
Nice to have
Experience with AI agent frameworks or orchestration tools
Exposure to prompt design and evaluation of AI model outputs
Familiarity with Agile delivery methodologies
Experience with observability, monitoring, and production support practices
Understanding of governance and compliance considerations for AI solutions