We are looking for a seasoned AI Architect to lead the end-to-end design and enterprise-scale deployment of cutting-edge AI solutions, with a deep focus on Generative AI (GenAI), Large Language Models (LLMs), and AI Agent frameworks. As a strategic technical leader, you will drive AI architecture decisions across cloud-native environments, build intelligent automation pipelines, and collaborate with both technical and executive teams to align AI initiatives with business strategy. You will be expected to bring a strong mix of hands-on delivery expertise and architectural leadership.
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Responsibilities
- Architect, build, and deploy production-grade AI/ML models with a strong focus on GenAI, LLMs, and intelligent agents.
- Serve as a lead architect across multiple cross-functional teams delivering AI-enabled applications.
- Design scalable, cloud-native AI solutions using the company Cloud Infrastructure (OCI) and other multi-cloud platforms.
- Mentor teams on solution design, best practices, and delivery excellence for AI projects.
- Guide enterprise-wide AI architecture strategy, ensuring alignment with data strategy, DevOps, and security best practices.
- Engage with C-suite stakeholders to define AI priorities, value propositions, and roadmaps.
- Lead solution estimation, technical governance, and program oversight.
- Contribute to GTM initiatives, including customer-facing demos and proposal development.
- Stay current with the latest advancements in GenAI, LLM optimization, AI agent architectures, and model integration strategies.
- Publish internal whitepapers, present at leadership forums, and help grow the AI practice through coaching and community engagement.
Qualifications & Experience
- 8+ years of total experience, with 4+ years in AI/ML Engineering roles.
- Demonstrated experience leading end-to-end AI/ML solution design and production deployment.
- Proven track record in Generative AI, LLMs, NLP, and AI agent development.
- Expert in Python and familiar with modern ML/NLP frameworks: HuggingFace, LangChain, PyTorch, TensorFlow, etc.
- Experience fine-tuning LLMs for domain-specific applications (e.g., Q&A systems, auto-documentation, predictive insights).
- Hands-on experience building, scaling, and optimizing AI systems on OCI, with knowledge of hybrid/multi-cloud architectures.
- Strong knowledge of machine learning algorithms, prompt engineering, vector databases, and RAG pipelines.
- Familiar with MLOps, model governance, and CI/CD for ML workflows.
Core Competencies & Technical Expertise
- Enterprise Architecture & AI Strategy
- Application Development (with focus on integrating AI into existing stacks)
- Multi-cloud & Distributed Architecture (OCI expertise is a must; experience with AWS, Azure, or GCP also valuable)
- AI/ML Security & Compliance
- DevOps & Agile AI Delivery
- Integration & Data Engineering Strategy
- Stakeholder Engagement – including Executive Leadership
- Program Oversight & Governance
- Solution Design, Proposals, and Estimates
- Industry Vertical: Proficiency in at least one Industry vertical will be an added advantage.
