Agentic AI Lead

Contactx Resource Management; Pune District; On-site; INR 2,500,000 - 6,000,000; Full time

Job summary

Contactx Resource Management seeks an AGENTIC AI LEAD to provide senior technical leadership for enterprise-wide agentic AI platforms. You will own the AI technology roadmap, set governance standards, and guide autonomous workflows across domains.

You will mentor senior engineers and partner with executives to drive AI-driven transformation. The role requires 9–18 years in advanced software and AI, strong experience with multi-agent systems, and proven leadership in AI platform engineering on

Qualifications

• 9–18 years in advanced software engineering and AI at enterprise scale.
• Proven architect for agentic AI platforms across domains and geographies.
• Deep expertise in multi-agent systems, planning and reasoning.
• Hands-on mastery of LLMs, prompts, and learning loops.
• Experience with agent frameworks (LangChain, LangGraph, AutoGen, CrewAI).
• Knowledge of memory, data platforms, and enterprise governance.
• Experience deploying AI platforms on GCP with cost efficiency.
• Strong leadership in MLOps and AI platform engineering.

Responsibilities

• Provide technical leadership for vision and execution of agentic AI platforms.
• Own technology roadmap and guardrails for agent design and operation.
• Lead design of distributed, autonomous agent systems with human-in-the-loop.
• Architect reusable IP, accelerators, and playbooks for adoption.
• Champion Responsible AI, governance, privacy, and compliance.
• Build and mentor high-performing engineering teams.

Skills

AI leadership

Architectural design

Multi-agent systems

MLOps

LLM deployment

GCP expertise

Team leadership

Executive collaboration

Education

BE/B.Tech in CS

MTech/MS/MBA preferred

Tools

LangChain

LangGraph

AutoGen

CrewAI

PostgreSQL

Job description

Big 4 Hiring for AGENTIC AI LEAD (Immediate/45days/60 days joiners)

Notice Period: Up to 2 Months.

Agentic AI Lead – 9 to 18 Years

Roles & Responsibilities

• Provide enterprise-wide technical and strategic leadership for the vision, architecture, and execution of large-scale agentic AI platforms and solutions across multiple business lines and domains.
• Own the agentic AI technology roadmap, guiding long-term evolution of agent architectures, platforms, accelerators, and operating models aligned with business and industry strategy.
• Lead the design and governance of complex, distributed agentic systems, including multi-agent ecosystems, cross-domain orchestration, long-running autonomous workflows, and human-in-the-loop decision systems.
• Set architectural guardrails and engineering standards for agent design, orchestration, memory, state management, reasoning, planning, and failure recovery at enterprise scale.
• Act as the highest level of technical authority on agent behaviour and intelligence, taking oversight and accountability for reasoning strategies, planning algorithms, escalation logic, risk handling, and system trustworthiness.
• Architect highly composable AI systems that integrate LLMs, traditional ML models, enterprise tools, APIs, event-driven systems, data platforms, and cloud-native services into cohesive intelligent workflows.
• Drive large-scale enterprise integration, enabling agentic platforms to work seamlessly with legacy systems, core business applications, data ecosystems, and partner platforms.
• Define and institutionalize enterprise reference architectures, design patterns, reusable IP, accelerators, and engineering playbooks for agentic AI adoption.
• Champion Responsible AI at an enterprise level, embedding governance, explainability, risk controls, auditability, privacy, security, and regulatory compliance across platforms and solutions.
• Partner with executive stakeholders, business leaders, and enterprise architects to shape AI-driven business transformation, translating strategic objectives into scalable agentic capabilities.
• Oversee system performance and economics, driving optimization across quality, accuracy, latency, throughput, reliability, and cost at portfolio scale.
• Provide executive oversight for production operations, including incident management, systemic risk mitigation, platform resilience, and SLA adherence across mission-critical deployments.
• Build and lead high-performing agentic engineering teams, mentoring senior technologists, principal engineers, and architects, and setting a culture of technical excellence and innovation.
• Drive innovation, thought leadership, and external visibility, contributing to internal IP, accelerators, whitepapers, patents, conferences, and client-facing AI transformation initiatives.

Education

• BE / B.Tech in Computer Science, Engineering, or a related discipline
• Postgraduate qualification (M.Tech / MS / MBA preferred)

Required Experience & Technical Skills

• 9-18 years of overall experience in advanced software engineering and AI systems, including leading AI, GenAI, or autonomous agent initiatives at enterprise scale.
• Proven track record in architecting and scaling agentic AI platforms across multiple domains, teams, and geographies.
• Deep expertise in multi-agent systems, autonomous decision-making, planning and reasoning architectures, human-agent collaboration, and enterprise workflow automation.
• Advanced hands‑on and conceptual mastery of LLMs, prompt/program synthesis strategies, reasoning frameworks, evaluation methodologies, and continuous learning loops.
• Strong experience with agent frameworks and platforms (LangChain, LangGraph, AutoGen, CrewAI, etc.) with the ability to design custom enterprise-grade agent foundations beyond framework defaults.
• Expert‑level understanding of agent orchestration, including hierarchical/task-based planning, tool invocation strategies, exception handling, resilience patterns, and agent collaboration protocols without over‑dependence on LangChain/LangGraph-style abstractions.
• Deep knowledge of memory, state, and context management, including short‑term/long‑term memory, vector databases, knowledge graphs, session isolation, and lifecycle governance.
• Advanced experience with RAG systems, search relevance optimization, grounding strategies, hallucination mitigation, and enterprise knowledge integration.
• Demonstrated algorithmic and model stewardship, including evaluation frameworks, risk modelling, bias analysis, and continuous optimization.
• Extensive experience deploying and operating AI platforms on Google Cloud Platform (GCP) using scalable, secure, and cost‑efficient cloud‑native architectures.
• Experience working with Postgre database.
• Strong leadership in MLOps and AI Platform Engineering, including CI/CD, model and prompt lifecycle management, testing at scale, and controlled enterprise releases.
• Expertise in AI observability and governance, including telemetry, tracing, quality evaluation frameworks, explainability dashboards, and cost governance.
• Strong command of AI security, privacy, and regulatory compliance, aligning with enterprise policies, industry regulations, and Responsible AI standards.
• Preferred: Deep exposure to General Insurance (Health, Motor, Travel) or other regulated industries, with experience driving AI‑led transformation of core business processes.