Job Summary

We are seeking a GenAI candidate with 7+ years of experience to build GenAI solutions using LLMs, RAG, and Langchain to address real-world business problems. Design and implement autonomous agents capable of task planning, decomposition, and tool/API invocation

Key Responsibilities

- GenAI Solution Leadership: Lead the architecture, development, and delivery of enterprise
- GenAI solutions using LLMs, RAG, agentic AI, and orchestration frameworks to solve complex business problems.
- LLMOps and Production Operations: Establish model and prompt lifecycle practices covering versioning, evaluation, deployment, observability, monitoring, incident response, rollback, cost optimization, and continuous improvement.
- Automation and Orchestration: Design intelligent automation and multi-agent workflows for task planning, tool calling, API invocation, human-in-the-loop controls, and reliable execution of business processes.
- Cloud Platform Delivery: Architect, deploy, and optimize GenAI workloads on GCP and Azure using services such as Vertex AI, Azure OpenAI, container platforms, managed data services, and secure cloud-native components.
- Databricks and Data Integration: Integrate GenAI applications with Databricks, enterprise data platforms, vector stores, APIs, databases, file repositories, and event-driven services while maintaining data quality, lineage, and access controls.
- Cloud Service Integrations: Build reusable and secure integration patterns for REST APIs, microservices, SDKs, queues, identity services, enterprise applications, and internal platforms.
- Client Handling and Communication: Lead client discovery, solutioning workshops, architecture discussions, status reviews, risk and issue communication, and executive-ready presentations; translate business needs into practical technical roadmaps.
- Technical Governance and Team Leadership: Define engineering standards, security guardrails,
- Responsible AI controls, evaluation gates, and delivery documentation; mentor engineers and coordinate cross-functional cloud,



data, platform, and business teams.

Required Qualifications

- 7-14 years of experience in AI/ML, data engineering, cloud platforms, or software engineering, including hands-on experience with Generative AI and LLM systems.
- Solid expertise in LLMOps, RAG, Agentic AI, prompt engineering, model evaluation, observability, production monitoring, and automation frameworks.
- Hands-on proficiency in Python, REST APIs, microservices, containers, CI/CD, and enterprise system integration.
- Demonstrated experience delivering solutions on GCP and/or Azure, with working knowledge of Databricks, cloud data services, security, identity, and scalable deployment patterns.

Preferred Qualifications

- Strong client handling, consulting, communication, presentation, and stakeholder management.
- Experience with Databricks, vector databases, MLflow or equivalent lifecycle tooling, Kubernetes, and cloud-native integration services.
- Ability to lead solution design, proofs of concept, production rollout, operational readiness, and cross-functional delivery for enterprise GenAI programs.

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Disclaimer: The following serves as an informative reference for the tasks you may be required to perform. However, it does not constitute an integral component of your employment agreement and is subject to periodic modifications to align with evolving circumstances . Please Note : We appreciate the accuracy and authenticity of the information you provide, as it plays a key role in your candidacy. As part of the Background Verification Process, we may verify your employment, education, and other details. Please ensure all information is factual and submitted on time. For any assistance, your recruiter is available to support you.

📌 Principal Consultant-GenAI (Bengaluru)
🏢 Evalueserve
📍 Bengaluru