Forward Deployed Engineer

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