Manager, Forward Deployed Engineering Applied AI Agents

Sears KAIros | India (Remote / Hybrid)

Team: Sears KAIros, Applied AI Division — TransformCo

Location: Remote / Hybrid, India

Type: Full-time

About the Role

Sears KAIros, the Applied AI Division of TransformCo, is hiring a Manager, Forward Deployed Engineering – Applied AI Agents to lead a team building and deploying production AI agents across business operations.

This role sits at the intersection of AI engineering, product, operations, and business transformation.

You will work directly with business leaders and operating teams across areas such as Sears Home Services, Kenmore, Central Finance, customer operations, field service, and other functions to identify high-impact workflows and transform them using AI agents.

This is a hands-on engineering leadership role. You should be equally comfortable sitting with an operator to understand a workflow, reviewing an agent architecture with engineers, diagnosing why an agent is failing in production, and presenting measurable business impact to senior leadership.

The goal is not to build AI demos. The goal is to deploy AI systems that materially improve how the business operates.

What You'll Do

• Lead a team of Forward Deployed Engineers responsible for taking AI agents from workflow discovery through production deployment and continuous improvement.
• Partner directly with operators, analysts, planners, dispatchers, finance teams, customer-service teams, and business leaders to identify high-value AI opportunities.
• Translate ambiguous business problems into clear agent specifications, workflows, tools, integrations, data requirements, evaluations, and success metrics.
• Prioritize opportunities based on business value, feasibility, operational risk, and speed to impact.
• Stay hands-on with architecture, prototyping, debugging, evaluations, production issues, and design decisions.
• Guide engineers in building agents that reason, use tools, call APIs, retrieve enterprise context, execute workflows, and handle exceptions safely.
• Establish production standards for evals, observability, guardrails, human escalation, auditability, rollback, reliability, and failure recovery.
• Build continuous learning loops using production interactions, user feedback, failure analysis, and evaluation data.
• Measure and communicate business outcomes including cost reduction, productivity, cycle time, conversion, customer experience, compliance, quality, and manual workload reduction.
• Drive adoption with business teams and ensure deployed agents become part of day-to-day operations.
• Coach engineers on both technical execution and the ability to work effectively with business stakeholders.
• Develop reusable frameworks, patterns, and playbooks so each new AI deployment becomes faster and more reliable.
• Present progress, outcomes, risks, failures, and learnings to senior business and technology leadership.

What We're Looking For

• 8+ years of experience across software engineering, AI/ML, product engineering, enterprise systems, automation, or applied technology.
• 2+ years of engineering or technical team leadership experience, with demonstrated ownership of production systems and business outcomes.
• B.Tech / M.Tech / MBA from IITs, BITS, IIMs, or another strong academic institution.
• Strong understanding of modern LLMs and AI agents, including prompting, tool use, function calling, structured outputs, retrieval, memory, agent orchestration, evaluations, and monitoring.
• Experience building or leading development of production software involving APIs, enterprise data, integrations, and distributed systems.
• Strong technical judgment around architecture, reliability, security, failure handling, data flows, and production risk.
• Ability to work directly with non-technical operators and senior executives and translate between business problems and engineering solutions.
• Working proficiency with Python, TypeScript/JavaScript, SQL, cloud platforms, APIs, and enterprise data systems.
• Strong analytical ability and comfort using data to evaluate both AI performance and business impact.
• Excellent written and verbal communication.
• High ownership, intellectual curiosity, speed of execution, and willingness to personally dive into difficult problems.

Nice to Have

• Experience with MCP, Claude Code, OpenAI Agents SDK, Anthropic Claude, Gemini, LangChain, LlamaIndex, or similar agent frameworks.
• Experience building AI systems involving multi-agent orchestration, computer use, browser automation, voice, or real-time interactions.
• Experience with field service, logistics, supply chain, contact centers, retail, finance operations, workforce operations, or customer experience.
• Experience with voice agents, telephony, speech-to-text/text-to-speech, or real-time APIs.
• Experience establishing evaluation and observability systems for production LLM applications.
• Prior experience in forward deployed engineering, solutions engineering, enterprise AI, consulting, or technology transformation.

Ideal Candidate

The ideal candidate is a builder-leader.

You can spend the morning with an operations team understanding why a process breaks, work with engineers in the afternoon to redesign the agent, inspect production failures in the evening, and clearly explain the business impact and next steps to leadership.

You are comfortable operating with ambiguity, moving quickly, learning from production, and changing direction when the evidence changes.

You believe the future of enterprise AI will be built not through isolated prototypes, but through reliable AI agents deeply integrated into real business workflows.

This role is for someone who wants to lead that transformation.