Lead - AI/ML Engineer (Generative AI Agent Systems)

Accountabilities:

• Lead Generative AI strategy and advisory: Serve as the primary technical SME for Generative AI, LLM reasoning patterns, autonomous agents, and agentic workflows, advising enterprise clients and senior stakeholders on technical direction and solution feasibility.
• Drive client-facing architecture: Translate complex business requirements into technical blueprints and architectural strategies, leading technical discovery sessions, solution assessments, and pre-sales engagements.
• Define reusable AI delivery practices: Establish playbooks, engineering patterns, and reusable frameworks that enable consistent and scalable deployment of agentic solutions across different clients and industries.
• Own agent reference architecture: Define the technical vision for production-ready agent frameworks, including Go-based harness patterns and solutions leveraging the Vertex AI Agent Development Kit.
• Lead agent design and delivery: Establish detailed agent specifications covering function calling and tool definitions, prompt engineering, context and input data models, and operational behaviors.
• Design autonomy and human oversight: Define graduated-autonomy models that balance autonomous execution with appropriate human-in-the-loop controls and exception handling.
• Build resilient distributed systems: Establish patterns for idempotency, event-driven communication, canonical event envelopes, and reliable interactions across bounded contexts.
• Develop AI evaluation and safety frameworks: Design continuous shadow-mode evaluation systems that assess agent performance against production-like data without creating real-world side effects.
• Define production-readiness criteria: Establish precision and recall thresholds, safety-critical test suites, model evaluation practices, and other quality gates required before agents graduate to production.
• Support AI governance: Partner with client governance stakeholders on model versioning, service classification, security controls, monitoring, and model or data drift management.
• Accelerate PoC delivery: Oversee or directly contribute to the initial shadow-mode proof of concept, helping establish a strong technical foundation for subsequent implementation.
• Lead technical delivery teams: Provide technical direction and mentorship while influencing architecture, engineering quality, delivery standards, and client outcomes across complex consulting engagements.

Requirements

• Professional experience: 6–12 years of experience in professional services, technology consulting, or similar environments, with demonstrated success leading technical delivery teams and working with senior client stakeholders such as CTOs and VPs of Architecture.
• Generative AI expertise: Deep, hands-on experience designing and deploying production-grade AI agent systems, multi-agent frameworks, LLM-backed reasoning loops, and autonomous workflows.
• Google Cloud expertise: Expert knowledge of the Vertex AI ecosystem, including Agent Engine, Agent Development Kit, model tuning, and Vector Search, combined with strong understanding of enterprise GCP security architectures.
• Cloud security: Experience with technologies and patterns such as VPC Service Controls, IAM, Pub/Sub, and secure cloud environments, particularly where strict security and compliance requirements apply.
• Software engineering: Advanced proficiency in Go (Golang), with strong experience developing highly concurrent, distributed, and event-driven backend systems.
• Agent architecture: Strong understanding of agent design, tool/function calling, prompt engineering, context management, evaluation methodologies, and human-in-the-loop architectures.
• Responsible AI: Experience or strong understanding of AI safety, governance, observability, model version management, evaluation, and production monitoring.
• Regulated environments: Experience working with highly regulated industries such as healthcare, financial services, or the public sector, where compliance, security, auditability, and controlled data access are critical.
• Consulting mindset: Strong ability to translate business problems into technical strategies and communicate complex AI concepts effectively to both technical and non-technical stakeholders.
• Leadership and communication: Excellent stakeholder management, presentation, problem-solving, and influencing skills, with the ability to operate confidently in complex, fast-moving client environments.

Benefits

• Remote work: Opportunity to work remotely from India with a globally distributed team.
• High-impact projects: Work on challenging enterprise transformation initiatives involving Generative AI, autonomous agents, cloud platforms, and emerging technologies.
• Technical leadership: Opportunity to shape AI architecture, engineering standards, reusable frameworks, and responsible AI practices at enterprise scale.
• Professional growth: Exposure to complex client environments, senior stakeholders, and cutting-edge AI and cloud technologies.
• Innovation-focused culture: Work in an environment that values bold thinking, practical innovation, independence, and solving complex business challenges.
• Global collaboration: Partner with experienced technology professionals and enterprise organizations across industries and geographies.
• Inclusive workplace: Join a diverse and collaborative environment committed to equal opportunity and professional growth.