AI Technical Lead

SmartRecruiters, Inc.; Chennai District; On-site; INR 900,000 - 1,600,000; Full time

Job summary

Hitachi Solutions, Ltd. is seeking a senior AI/automation architect to own the end-to-end architecture of an AI-assisted migration platform, including agent/skill/harness design and Azure cloud architecture. You will drive AI/ML strategy, select models, and balance fidelity, cost, and performance.

You will lead a 3–8 person team and coordinate with client IT teams to define data requirements and backlogs. The role requires strong background in AI/LLM systems, parsing engines, and integration

Qualifications

• Must have strong software architecture experience for AI-enabled platforms.
• Experience delivering AI/automation solutions in enterprise environments.
• Ability to lead cross-functional teams and manage client expectations.

Responsibilities

• Own end-to-end architecture of AI-assisted migration platform.
• Drive AI/ML strategy including model selection and cost/latency trade-offs.
• Lead delivery and stakeholder management across feasibility to production.
• Mentor a 3–8 person AI/automation engineering team.
• Develop AI/LLM components and integrate with external APIs.

Skills

Node.js/TypeScript/Python

XML/JSON parsing

Parsers/ASTs/Rule engines

RAG/classification pipelines

Agent/Skill/Harness design

AI/LLM prompting & tooling

Eval harness/model scoring

OAuth/Azure AD authentication

Education

B.E/B.Tech/M.Sc. Computers/MCA

Tools

Nintex

Power Automate

Azure OpenAI

Anthropic/OpenAI API

Job description

Hitachi Solutions, Ltd., headquartered in Tokyo, Japan, is a core member of Information & Telecommunication Systems Company of Hitachi Group and a recognized leader in delivering proven business and IT strategies and solutions to companies across many industries. The company provides value-driven services throughout the IT life cycle from systems planning to systems integration, operation and maintenance. Hitachi Solutions delivers products and services of superior value to customers worldwide through key subsidiaries in the United States, Europe, China and India. The flagship company in the Hitachi Group's information and communication system solutions business, Hitachi Solutions also offers solutions for social innovation such as smart cities.

Our Competitive Edge

We work together in a dynamic and rewarding work environment. We have an experienced leadership team, excellent technology and product expertise, and strong relationships with a broad base of customers and partners.

We offer competitive compensation and benefits package, regular performance review, performance bonuses, and regular trainings.

What is it like working here?

We pride ourselves on being industry leaders and providing an enjoyable work environment where our people can grow personally and professionally. Hitachi is the place people can develop skills they’re excited about. The following are our commitments to employees.

• We recognize our profitability and project success comes from our team—great people doing great things. As such, we pursue profitable growth and expanded opportunities for our team.
• We offer challenging and diverse work across multiple industries and reward creativity and entrepreneurial innovation.
• We respect, encourage, and support each individual needs to continually learn and grow personally and professionally. We are committed to fostering our people.
• We listen. Every employee has something important to say that can contribute to enriching our environment.
• We compensate fairly. And while employees might come for the paycheck, they stay for the people. Our people are the reason we are exceptional. This is something we never forget.

Job Description

Own the end-to-end architecture of the AI-assisted migration platform — agent/skill/harness design, AI-in-the-loop bounding of LLM output, and Azure cloud architecture (App Services, Functions, Key Vault, Azure AD).

Drive AI/ML strategy: build-vs-buy and model selection calls, fine-tuning vs. prompting and cost/latency trade-offs, and definition of fidelity scoring and gap-analysis evaluation metrics.

Lead delivery and stakeholder management — scope feasibility studies vs. production builds, define data requirements with customer IT teams, and triage client edge-case escalations into a prioritised backlog.

Lead and mentor a 3–8 person AI/automation engineering team across classical and prompt-engineering disciplines, while owning migration risk, rollback strategy, and security/credential review.

Develop AI/LLM components — prompt engineering with schema-constrained output, LLM API integration (Anthropic/OpenAI/Azure OpenAI), and RAG or classification pipelines that map legacy actions to modern equivalents.

Integrate the solution with the surrounding ecosystem via REST APIs, webhooks, Azure CLI/Azure AD authentication flows, and MCP server endpoints.

Own quality through automated workflow validation tests and eval harnesses that score model output fidelity, and document unsupported or manually reviewed conversion cases.

Build and maintain the parsing/conversion engine (Node.js/TypeScript or Python) that reads XML/JSON-based Nintex workflow definitions and generates equivalent Power Automate flow logic.

AI Developing Skill:

Core Programming & Parsing

• Node.js / TypeScript or Python (framework matching the Agent's stack)
• XML/JSON parsing experience (Nintex NWF is XML-based)
• Experience building parsers, ASTs, or rule engines
• RAG or classification pipeline experience
• Coding Agent experience via Claude / Github copilot
• Eval-harness / model output scoring experience

Integration / Ecosystem

Testing & Quality

• Test automation for workflow/flow validation

Nice to Have (General)

All Developer-level skills (Full Developer Skills Matrix (see 'Developer Skills' tab))

• Designs multi-stage for AI Coding Architectures (Agents, Skills, Harness Engineering)
• Experience architecting AI-in-the-loop systems (bounding LLM output, hallucination/fidelity risk)
• Build-vs-buy calls on model selection, fine-tuning vs. prompting, cost/latency tradeoffs
• Defines evaluation metrics for a generative system (fidelity scoring, gap analysis frameworks)

Delivery & Stakeholder Management

• Has scoped feasibility studies vs. production builds
• Client-facing experience; triages edge-case escalations into a backlog
• Defines data requirements with customer IT teams (logs, connector inventories, run history)
• Migration risk management (unsupported actions, rollback strategy)
• Security review experience (auth handling, credential migration, connection ownership)

Leadership

• Has led a small-to-mid AI/automation engineering team (3–8 devs)
• Mentors across both classical engineering and AI/prompt-engineering skill sets

Qualifications

B.E/B.Tech/M.Sc. Computers/MCA