Forward Deployment Engineer

Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients’ most complex digital transformation needs. Leveraging our holistic portfolio of capabilities in consulting, design, engineering, and operations, we help clients realize their boldest ambitions and build future-ready, sustainable businesses. With over 230,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world.

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Job Description:

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

• 4–8 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/Type Script, 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, Service Now, Microsoft Dynamics or similar platforms.
• Familiarity with data engineering, ETL/ELT pipelines, BI dashboards, analytics, and reporting workflows.
• Healthcare…