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Forward Deployed Engineer - USA (Remote)

Nityo Infotech CorporationUnited States🇺🇸United StatesPosted 8 Sept 2026

Why This Role Stands Out

This remote Forward Deployed Engineer role offers a unique opportunity to directly impact business outcomes by building and deploying AI-led automation, allowing you to grow your skills across engineering, product thinking, and consulting. You'll thrive here if you're a hands-on builder eager to embed within business units, solve complex problems, and drive measurable AI innovation in a dynamic, collaborative environment.

Quick Overview

Seniority
Mid Senior
Work mode
Remote
Location
United States
Posted
Yesterday
Jira

Job Description

Job Title: Forward Deployed Engineer (FDE)

Location: USA - Remote

We are looking for a Forward Deployed Engineer (FDE) who partners directly with UHG business teams to identify high-value problems and deliver AI-led automation and innovation under centralized council oversight.

An FDE in UHG is an empowered AI builder embedded within business units to understand real-world context, build practical solutions, and drive measurable AI driven outcomes.

The role blends hands-on engineering, solution architecture, product thinking, consulting, and customer-facing execution.

Key Responsibilities:
1. Business Embedding and Outcome Ownership

  • Embed with business and engineering teams to own AI outcomes within a defined business domain.
  • Build and deliver AI solutions hands-on; this is an execution role, not an advisory role.
  • Convert AI potential into production value through code-first delivery and active repository contributions.

2. Problem Discovery and Solution Design

  • Understand business processes, pain points, systems, data flows, and success metrics.
  • Translate problems into MVPs, integrations, automations, and production-ready solutions with an ownership mindset
  • Build across APIs, databases, cloud platforms, workflow tools, enterprise systems, and AI/GenAI technologies.

3. Rapid Prototyping and Value Validation

  • Own the journey from discovery to working solution, rapidly proving business value through pilots and POCs

4. Integration, Adoption, and Scale

  • Integrate with enterprise platforms, data systems, workflows, collaboration tools, and third-party APIs.
  • Document architectures, implementation playbooks, reusable components, and customer-specific solution guides.
  • Feed field learnings into product roadmap, accelerators, and go-to-market propositions.

Required Skills and Experience:

  • 5-10 years of experience in AI led engineering, implementation, product, consulting, or customer-facing technology roles.
  • Strong engineering fundamentals with hands-on coding experience in Python, JavaScript/TypeScript, Java, .NET/C#, or Go.
  • AI proficiency is mandatory; candidates may come from software engineering, data science, UX, or related domains with proven hands on experience.
  • Daily AI tool usage, demonstrable code contributions, and documented token usage.
  • Strong analytical thinking and expertise in effectively utilizing data to derive AI solutions to solve business problems.
  • Strong understanding of APIs, databases, cloud services, authentication, integrations, and deployment.
  • Experience in Data and analytics platforms.
  • Comfortable with structured and unstructured data.
  • Experience with GenAI, LLMs, RAG, agents, AI workflow automation, prompt engineering, model integration and model training.
  • Cloud experience across AWS, Azure, or Google Cloud.
  • Good communication, adaptability, and problem-solving in ambiguous environments.

Good to Have:

  • Knowledge of ML algorithms, model building, deployment, deep learning, and NLP.
  • Experience integrating with Salesforce, Jira, Rally, Oracle, ServiceNow, Microsoft Dynamics or similar platforms.
  • Familiarity with data engineering, ETL/ELT pipelines, BI dashboards, analytics, and reporting workflows.
  • Healthcare exposure, especially contact centers, claims automation, finance, or technology services.

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