Forward Deployed Engineer (Spec-Driven Test Generation and Automation)

Job Description

Role: Forward Deployed Engineer (Spec-Driven Test Generation and Automation)

Location/mode: On-Site- Berkeley Height, NJ

Experience: 10+ years in software engineering and solution engineering, 2–3 years in AI Engineering

Role Summary

Forward Deployed Engineer (FDE) who can connect business needs with technology solutions through AI-assisted engineering, automation, and contemporary software delivery practices.

In this role, you will partner directly with customers to turn their business requirements into scalable, well-engineered solutions. By applying AI-native engineering methods, Agentic SDC practices, and automation frameworks, you will speed up solution delivery while maintaining enterprise-grade quality and governance. The ideal candidate will design and deploy solutions using AI/SDC (spec-driven development).

Key Responsibilities

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• Work closely with customers and stakeholders to understand business goals, strategy, pain points, and operational needs.
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• Design technology solutions, AI/agent workflows, integrations, data requirements, security and risk requirements.
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• Build AI agents, copilots, applications, APIs, services, integration with enterprise systems, RAG, orchestration.
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• Design, generate and validate AI-generated code and engineering artifacts, and drive deployment of enterprise-grade applications, integrations, and AI-powered solutions.
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• Apply prompt engineering, context engineering, and AI enablement techniques to improve solution outcomes.
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• Customize SDD framework (GitHub SpecKit) to implement or enhance the application functionality.
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• Build the code analysis capability that scans the application code base (UI components, routes, controllers/services, API definitions, data models, validation and business-rule logic) using SOD framework .
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• Extract user flows, functional rules, boundary conditions, error paths, and integration points from the code using SDD framework.
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• Convert the extracted understanding into structured, reviewable specs using the SpecKit workflow (specification, clarify, plan, tasks, implement).
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Additional Responsibilities

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• Handle large or legacy code bases through chunking, indexing, dependency mapping, and context management so results stay accurate.
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• Review and validate AI-generated test designs, test cases, Playwright automation scripts, and production readiness.
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• Be able to generate functional, negative, boundary, and regression test cases from both specs and code-derived specs.
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• Generate and maintain test automation scripts using Page Object Model , reusable fixtures, and API-level tests alongside UI tests.
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• Tune prompts, templates, and guardrails so generated scripts follow correct coding standards (stable locators, test data handling, minimal flakiness).
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• Validate generated scripts by executing them and feeding failures back into generation.
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• Wire the flow into GitHub Actions or the client's CI/CD tooling: scan, spec generation, test generation, execution, reporting.
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• Work embedded with client teams to assess their applications, documentation state, and automation maturity.
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• Run pilots, demos, and enablement sessions, and document how to use and extend the solution.
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• Help client QA and developers review and approve AI-generated outputs, keeping a human in the loop.
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• Gather feedback, prioritize improvements, and escalate risks early.
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Required Skills

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• Spec-driven development: Working knowledge of GitHub Spec Kit or comparable approaches.
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• AI/LLMs: Practical experience with LLMs and AI coding assistants, including prompt engineering, structured outputs, context handling for large code bases, guardrails, and evaluating output quality.
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• Primary Coding Language: Python.
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• Code comprehension: Ability to read and reason about code in the client's stack (for example Java/Spring, .NET, Node.js or Python), including REST APIs and data models.
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• Code analysis: Experience with static analysis or code parsing technologies (AST parsing, dependency analysis, or tools such as Tree-sitter, CodeQL, or SonarQube).
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• GitHub: Experience with GitHub workflows and GitHub Actions.
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• Communication: Strong ability to explain technical decisions to engineers and business stakeholders.
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Professional Skills

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• Strong problem-solving and analytical capabilities.
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• Customer-facing communication and consulting skills.
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• Ability to work independently in fast-paced environments.
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• Experience collaborating with cross-functional and distributed teams.
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• Strong ownership mindset with a focus on measurable business outcomes.
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