Senior Forward Deployed Engineer (FDE)

Tranzeal Inc.

  • Palo Alto, CA
  • 30+ days ago

    Highlights

    databases, retrieval optimizations, multi-modal systems, evaluation frameworks, GPU/Infra trends, fine tuning techniques, security/guardrails and broader landscape of. Solid understanding of LLMs, Prompt engineering/tuning, Vector DBs (AstraDB, Pinecone, Weaviate etc), RAG pipelines (LlamaIndex, Haystack) and Agent/Workflow.

    Numbers & Facts

    LocationPalo Alto, CA

    Description

    Job Title: Senior Forward Deployed Engineer (FDE)
    Location: Hybrid, Palo Alto, CA

    As a Senior Forward Deployed Engineer (Sr. FDE) at Uniphore, you will take technical
    ownership of strategic AI solution deployments and lead the architecture, prototyping, and
    delivery of customer-specific applications on our Agentic AI platform. This role demands a deep
    technical skillset, sharp solution thinking, and the ability to guide both customers and internal
    teams through complex, high-stakes AI projects.
    You're not just coding - you're solving some of the most exciting challenges and problem solving
    in enterprise AI rollout, spanning enterprise data pipelines, multi-agent
    orchestration/workflows and RAG/SLM finetuning.
    Responsibilities
    Lead the technical solution design and implementation of large-scale Agentic and
    Knowledge AI solutions for key enterprise clients.
    Act as the primary technical point of contact during solution development and post-
    deployment optimization.
    Own and execute projects end-to-end: from integration design to agent workflows and
    full-stack delivery.

    Customize platform components as needed—integrating new APIs, building reusable
    tooling, or extending platform logic.
    Collaborate closely with cross-functional teams internally and with customers to ensure
    solution success.
    Provide structured feedback to Platform Engineering and Product on feature gaps and
    customer pain points.
    Contribute to technical best practices and accelerate solution delivery through reusable
    assets, frameworks, and documentation.
    Champion observability, monitoring, versioning and telemetry to ensure trustworthy
    and auditable AI agents.
    Stay current on RAG, LLM/SLM advancements, Agentic AI tooling, vector/graph
    databases, retrieval optimizations, multi-modal systems, evaluation frameworks,
    GPU/Infra trends, fine tuning techniques, security/guardrails and broader landscape of
    Enterprise & Agentic AI.
    Qualifications
    Undergraduate, master's degree or Phd in Computer Science or Data Science
    6–10+ years of experience in engineering, with 2+ years in customer-facing or field roles.
    Proven success building and deploying AI/ML or data-intensive applications in
    production.
    Deep full-stack development skills (Python, Node.js/Go, React/Vue) and DevOps
    experience (Docker, K8s, CI/CD).
    Expertise in building data pipelines and integrating with enterprise systems (REST,
    Python, SQL, GraphQL, Webhooks etc).
    Solid understanding of LLMs, Prompt engineering/tuning, Vector DBs (AstraDB,
    Pinecone, Weaviate etc), RAG pipelines (LlamaIndex, Haystack) and Agent/Workflow
    Orchestration (LangChain, LangGraph, CrewAI)
    Knowledge of SLM Finetuning and Distillation is big advantage.
    Experience and knowledge of Agentic development platforms and experience building
    and delivery enterprise agentic solutions is a huge advantage.
    Ability to translate ambiguous customer needs into actionable engineering plans.
    Strong leadership, mentoring, and project ownership abilities.
    Excellent communication and collaboration across technical and business stakeholders.

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