Specialist II - ML Engineering

Exp: 13yrs-20yrs
Location: Tvm, Kochi, Bangalore, Chennai,Hyderabad
NP: only Immediate- 30days (no profiles with 90 days or 60 days neg to 30days)
Summary: Lead architecture and delivery of enterprise-grade Generative AI solutions, partnering with business stakeholders to translate use cases into secure, compliant, and scalable production systems. Drive governance, innovation, and capability building across India and global teams.
Key Responsibilities

• Solution Architecture & Delivery: Architect, design, and deliver robust, scalable GenAI solutions across discovery, development, regulatory, and commercial domains; own end-to-end delivery and production health (performance, reliability, security).
• Reference Architecture & Reuse: Define and maintain enterprise reference architectures, reusable components, patterns, and best practices that accelerate GenAI adoption and reduce time-to-value.
• Business Partnership & Value Creation: Work closely with stakeholders to identify and prioritize high?value GenAI use cases; translate business needs into practical technical solutions that balance innovation and feasibility.
  
• Governance, Compliance & Responsible AI: Ensure solutions embed responsible AI principles (transparency, fairness, privacy, security); implement model/data governance, lifecycle standards, and regulatory compliance controls.
• Innovation & Ecosystem Leadership: Evaluate and pilot emerging LLMs, frameworks, and orchestration tools (for example OpenAI, Anthropic, Llama, LangChain, LlamaIndex); cultivate partnerships with vendors, startups, and academia.
• Proofs-of-Concept & Adoption: Lead POCs and pilots, demonstrate business impact, and champion adoption of effective GenAI capabilities across the organization.
• Technical Leadership & Capability Building: Provide hands?on guidance and mentorship to engineering teams; develop training, documentation, and communities of practice to grow long?term GenAI capability across the India hub and global teams.
• Operational Readiness: Define monitoring, incident response, cost controls, and SRE/ops practices for GenAI services in multi?cloud environments.
  

Minimum Qualifications

• Education: Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or related field.
• Experience: 13+ years in enterprise IT, solution architecture, or engineering leadership with multiple AI/ML/GenAI delivery projects.

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• Technical Expertise: Deep hands?on experience with LLMs and agent architectures, vector databases, RAG/Retrieval pipelines, and multi?agent systems.
• Cloud & Deployment: Proven ability to design and deliver solutions across multi?cloud platforms (e.g., Azure AI Foundry, AWS AI services, Google/Vertex/Gemini ecosystem).
• Delivery & Governance: Strong track record of delivering production systems with attention to security, compliance, model lifecycle management, and data privacy.
• Communication & Leadership: Excellent stakeholder management, influencing skills, and ability to lead cross?functional teams.
  

Preferred Qualifications

• Research & Tools: Familiarity with LangChain, LlamaIndex, DSPy or similar orchestration/LLM tooling; experience evaluating LLM model families and cost/performance trade-offs.
• Ecosystem Experience: Established partnerships or experience collaborating with AI vendors, startups, or academic research groups.
• Operationalization: Experience building deployment pipelines, model monitoring, drift detection, and automated retraining workflows.