Uniphore
Senior Forward Deployed Engineer

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Senior Forward Deployed Engineer
About the Role 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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I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
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StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
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