Forward Deployment Engineer – R01565619
Listed on 2026-06-02
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Software Development
AI Engineer, Cloud Engineer - Software, Software Engineer, Full Stack Developer
Jersey City, United States
Job : R
Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world‑class professionals, referred to as "Brillians", distinguishes itself through its capacity to seamlessly integrate cutting‑edge digital and design‑thinking skills with an unwavering dedication to client satisfaction.
Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its emphasis on contemporary, groundbreaking technologies and exclusive digital projects. Brillio's commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners it the Great Place to Work® certification year after year.
Primary Skills- AWS, Python, and Claude (and related AI/agent stacks)
- Product Management:
Software Development Manager
Years of
Experience:
10+ years
As a consultant within the DE team, you will work with our clients to define their digital strategy and execution roadmap, and design and implement differentiated digital solutions to help deliver measurable value.
Job Description:
Role Overview
We are looking for Forward Deployment Engineers (FDEs) to work directly with customer business and technology teams to design, build, and deploy AI-driven solutions that transform real-world workflows. This is a hybrid role requiring both product thinking (problem discovery, requirements, success metrics) and hands‑on engineering (rapid prototyping through to production deployment). The ideal candidate is comfortable operating under ambiguity, embedding customer teams, and delivering measurable outcomes using AWS, Python, and Claude (and related AI/agent stacks).
Key Responsibilities1) Product Discovery & Solution Shaping (PM capability)
Partner with customer stakeholders to understand current workflows, pain points, constraints, and desired outcomes.
Translate business objectives into a clear delivery plan: requirements, user stories, acceptance criteria, and roadmap from prototype to scaled deployment.
Define success metrics (e.g., cycle‑time reduction, automation rate, accuracy, adoption) and drive alignment through regular demos and updates.
2) Forward‑Deployed Execution (Client‑embedded delivery)
Embed with client teams to whiteboard solutions, build prototypes quickly, deploy, and iterate based on feedback.
Own outcomes end‑to‑end— from discovery to production release, stabilization, and continuous improvement.
Troubleshoot issues in real environments and ensure solutions are reliable, maintainable, and aligned to business needs.
3) Hands‑on Engineering (AWS + Python)
Build production‑grade services, APIs, and workflow integrations using Python (and associated libraries/frameworks).
Design and deploy cloud‑native components on AWS (serverless and/or container‑based architectures as appropriate).
Apply strong engineering practices: testing, CI/CD, logging/monitoring, performance tuning, and security‑by‑design.
4) AI / Agentic Solutions using Claude (and related stacks)
Build production applications leveraging Claude to solve real business problems in customer environments.
Develop and deliver reusable technical artefacts that support AI workflows (e.g., agents/sub‑agents, skills, integration components) used in production.
Identify repeatable deployment patterns and share learnings with internal teams to improve future delivery and scalability.
5) Enablement & Adoption ("Teach the business to fish")
Enable customer teams to use and extend solutions independently through training, playbooks, documentation, and operational runbooks.
Drive adoption by aligning stakeholders, supporting change management, and ensuring solutions fit real operating models.
Skills & Qualifications (Must Have)
- Strong software engineering fundamentals with hands‑on Python experience (APIs, microservices, automation).
- Strong hands‑on experience building and deploying solutions on AWS.
- Experience building LLM‑powered…
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