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Forward Deployed Engineer; Spec-Driven Test Generation and Automation

Job in Berkeley Heights, Union County, New Jersey, 07922, USA
Listing for: Envision Technology Solutions
Full Time position
Listed on 2026-10-11
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Software Engineer, Python, Software Testing
Salary/Wage Range or Industry Benchmark: 150000 - 190000 USD Yearly USD 150000.00 190000.00 YEAR
Job Description & How to Apply Below
Position: Forward Deployed Engineer (Spec-Driven Test Generation and Automation)

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

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

  • Work closely with customers and stakeholders to understand business goals, strategy, pain points, and operational needs.
  • Design technology solutions, AI/agent workflows, integrations, data requirements, security and risk requirements.
  • Build AI agents, copilots, applications, APIs, services, integration with enterprise systems, RAG, orchestration.
  • Design, generate and validate AI-generated code and engineering artifacts, and drive deployment of enterprise-grade applications, integrations, and AI-powered solutions.
  • Apply prompt engineering, context engineering, and AI enablement techniques to improve solution outcomes.
  • Customize SDD framework (Git Hub Spec Kit) to implement or enhance the application functionality.
  • 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.
  • Extract user flows, functional rules, boundary conditions, error paths, and integration points from the code using SDD framework.
  • Convert the extracted understanding into structured, reviewable specs using the Spec Kit workflow (specification, clarify, plan, tasks, implement).

Additional Responsibilities

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

Required Skills

  • Spec-driven development: Working knowledge of Git Hub Spec Kit or comparable approaches.
  • 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.
  • Primary Coding Language: Python.
  • 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.
  • Code analysis: Experience with static analysis or code parsing technologies (AST parsing, dependency analysis, or tools such as Tree-sitter, CodeQL, or Sonar Qube).
  • Git Hub: Experience with Git Hub workflows and Git Hub Actions.
  • Communication: Strong ability to explain technical decisions to engineers and business stakeholders.

Professional Skills

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