Lead - AI/ML Engineer (Generative AI Agent Systems)
New
J
JobgetherAI/ML Consulting
Remote from IndiaContractLead
Salary not disclosed
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Job Details
- Experience
- 6–12 years
- Required Skills
- GCPGoLLMGenerative AIDistributed Systems
Requirements
- 6–12 years of professional experience in technology consulting or similar environments.
- Demonstrated experience leading technical delivery teams and managing senior client stakeholders (CTOs, VPs of Architecture).
- Deep, hands-on experience designing and deploying production-grade AI agent systems.
- Expertise in multi-agent frameworks, LLM reasoning loops, and autonomous workflows.
- Expert knowledge of the Google Cloud Vertex AI ecosystem including Agent Engine and Vector Search.
- Advanced proficiency in Go (Golang) for developing concurrent, distributed backend systems.
- Strong understanding of agent architecture, tool calling, prompt engineering, and human-in-the-loop systems.
- Knowledge of cloud security technologies including VPC Service Controls, IAM, and Pub/Sub.
- Experience with AI safety, governance, model version management, and production observability.
- Experience working within regulated industries such as healthcare, finance, or the public sector.
Responsibilities
- Lead Generative AI strategy and advisory for enterprise clients and senior stakeholders.
- Translate business requirements into technical blueprints and architectural strategies.
- Establish reusable delivery frameworks, engineering patterns, and playbooks for agentic solutions.
- Design production-ready agent frameworks leveraging Go and the Vertex AI Agent Development Kit.
- Define agent design specifications including function calling, tool definitions, and context management.
- Establish graduated-autonomy models with human-in-the-loop controls and exception handling.
- Build resilient distributed systems with event-driven communication and reliable interaction patterns.
- Develop AI evaluation and safety frameworks including continuous shadow-mode assessment.
- Define production-readiness criteria such as precision, recall, and safety-critical test suites.
- Lead technical delivery teams, providing direction and mentorship across complex consulting engagements.
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