Uniphore is looking to solve complex challenges in enterprise AI by deploying strategic AI solutions for key enterprise clients on their Agentic AI platform. This involves building and delivering customer-specific applications that leverage Generative AI, Knowledge AI, and Emotion AI.
Requirements
- 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, and RAG pipelines.
- 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.
- Proven success building and deploying AI/ML or data-intensive applications in production.
- Stay current on RAG, LLM/SLM advancements, Agentic AI tooling, and industry trends relevant to Enterprise & Agentic AI.
Responsibilities
- Contribute to the technical 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.
- Guide junior FDEs and collaborate closely with cross-functional teams 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.
Other
- 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.
- 3+ years of experience in engineering, with 1+ years in customer-facing or field roles.
- Undergraduate, master’s degree or Phd in Computer Science or Data Science
