What are the responsibilities and job description for the Forward Deployed Engineer position at Lorven Technologies, Inc.?
Hi,
Our client is looking for an Forward Deployed Engineer in Remote, below is the detailed requirement.
Our client is looking for an Forward Deployed Engineer in Remote, below is the detailed requirement.
Job positing Title: Forward Deployed Engineer
Location: Remote
Job description:
- We are looking for a Forward Deployed Engineer (FDE) who partners directly with business teams to identify high-value problems and deliver AI-led automation and innovation under centralized council oversight.
- An FDE in 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:
- 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.
- 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.
- Rapid Prototyping and Value Validation
- Own the journey from discovery to working solution, rapidly proving business value through pilots and POCs
- 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.
- 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.