Forward Deployed Engineer

Accellor

. Develop features, resolve defects, refactor applications, and create automated tests using AI-assisted development tools .

Posted 11/3/2026full-timeRemote • United StatesMid-LevelSenior💰 $90,000 - $130,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates proficiency in software engineering and AI development, with strong skills in prompt engineering, automated testing, and collaboration across teams. Capable of managing coding workflows, ensuring code quality, and optimizing AI-assisted development processes.

Highest-signal resume keywords

Proficiency In Python, TypeScript, Java, Go, Or C#Hands-On Experience With Cursor Or Comparable AI Coding EnvironmentsStrong Prompt Engineering SkillsWorking Knowledge Of Git, Pull Requests, And CI/CDExperience Developing Workflows With Multiple Coding Agents

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringAI EngineeringPrompt EngineeringAutomated TestingDebuggingAPIsCI/CDTask DecompositionModel EvaluationCode Review

Soft Skills

Clear CommunicationCollaborative Working HabitsOwnership Of Engineering Outcomes

Tools & Technologies

CursorOpenAI ModelsAnthropic ClaudeModel Context Protocol (MCP)Agent Orchestration FrameworksCloud PlatformsContainersDeployment AutomationApplication Observability

Industry Keywords

AI-Assisted DevelopmentSoftware DevelopmentEngineering ProductivityCost EfficiencyCoding Standards

Tech Stack

Tools & technologies

CloudJavaJavaScriptPythonTypeScriptGo

About the role

Key responsibilities & impact

Develop features, resolve defects, refactor applications, and create automated tests using AI-assisted development tools
Use Cursor and other coding environments for repository exploration, implementation, debugging, testing, and code review
Translate product requirements into engineering tasks, technical approaches, and acceptance criteria
Own code quality and delivery readiness, including changes produced by AI models or agents
Collaborate with product, engineering, and quality teams to deliver reliable software releases
Design and maintain prompts, repository instructions, context strategies, and reusable software-engineering workflows
Provide models with relevant architecture, dependencies, coding standards, constraints, and expected outcomes
Establish repeatable evaluations for correctness, consistency, requirement coverage, and human intervention needs
Improve prompts and workflows using test results, code reviews, and delivery outcomes
Build coordinated coding-agent groups for planning, implementation, testing, review, and documentation
Design task delegation, handover, takeover, and recovery workflows with clear ownership and shared task state
Manage parallel execution, dependencies, isolated workspaces, and integration conflicts
Define tool access, execution boundaries, and human review checkpoints
Ensure agent-produced changes are traceable, reviewable, tested, and integrated
Select models and tools based on task requirements, quality, latency, and cost
Optimize context size, token consumption, model routing, retries, and agent execution overhead
Establish baselines and measure development throughput, delivery time, review effort, and AI expenditure
Report weekly and monthly delivery trends, including pull requests raised and merged
Share validated practices and reusable tools that improve the wider engineering team’s effectiveness

Requirements

What you’ll need

0–4 years of relevant experience in software engineering, AI engineering, or applied AI development; academic, personal, and open-source projects will also be considered
Proficiency in at least one programming language, such as Python, TypeScript/JavaScript, Java, Go, or C#
Hands-on experience applying frontier models, including OpenAI models or Anthropic Claude, to software development
Practical experience with Cursor or comparable AI coding environments
Strong prompt engineering skills, including task decomposition, context preparation, structured outputs, and iterative evaluation
Working knowledge of Git, pull requests, debugging, automated testing, APIs, and CI/CD
Ability to understand existing codebases and independently assess the correctness of AI-generated code
Clear communication, collaborative working habits, and ownership of engineering outcomes
Preferred: experience developing workflows with multiple coding agents, including delegation, handover, and integration
Preferred: familiarity with model APIs, tool calling, Model Context Protocol (MCP), and agent orchestration frameworks
Preferred: experience evaluating prompts and models using defined datasets, acceptance criteria, and automated checks
Preferred: experience monitoring AI usage, engineering productivity, and cost efficiency
Preferred: exposure to cloud platforms, containers, deployment automation, and application observability
Preferred: portfolio of working software demonstrating effective use of AI tools, supported by tests and technical documentation

Benefits

Comp & perks

Flexible and discretionary time off
Healthcare coverage for you and your loved ones
Retirement savings plan
Flexible spending accounts
Health savings accounts
Life and AD&D insurance
Opportunities for professional development
Annual bonus may be available