AI Solutions Architect

Jupitice Justice Technologies Private Limited; Chandigarh; On-site; INR 1,500,000 - 2,000,000; Full time

Job summary

Jupitice Justice Technologies Private Limited is seeking an experienced AI Solutions Architect in Chandigarh. The role requires over 10 years of experience in AI and Machine Learning, with a strong emphasis on software development and AI-assisted techniques. Key responsibilities include designing software solutions, mentoring engineering teams, and establishing AI-driven practices. Candidates should possess expertise in modern programming languages and a solid understanding of system design and architecture. Interested applicants can contact [e-mail].

Qualifications

• 10+ years of experience in AI, Machine Learning, or related fields.
• Hands-on experience in building production software using AI tools.
• Demonstrated ability to lead engineering teams effectively.

Responsibilities

• Design and deliver software solutions using AI-assisted development.
• Implement coding standards and review AI-generated code.
• Mentor engineers to adopt AI-driven workflows.

Skills

AI-driven development

Team Leadership

System Design

Coding proficiency

AI tooling

Tools

Node.js

Python

SQL

CI/CD

Job description

AI Solutions Architect

Chandigarh 10+ Years Experience

Role Overview

This role is designed for a practitioner who has evolved from deep experience in Artificial Intelligence into hands‑on, production‑grade software development using AI‑assisted methodologies. The individual is expected to architect, build, and deliver robust, scalable products by leveraging AI not merely as a support tool, but as a core development paradigm.

In addition to technical excellence, this role carries a strong leadership mandate—to institutionalize AI‑driven development practices and actively elevate the capabilities of the broader engineering team.

Key Responsibilities

AI‑Native Product Development

• Design and deliver end‑to‑end software solutions using AI‑assisted development workflows.
• Translate business problems into scalable system architectures and working products.
• Own delivery from concept → prototype → production.

AI‑Assisted Engineering Practices

• Use advanced AI tools (LLMs, agents, code generation systems) to accelerate development while maintaining code quality and architectural integrity.
• Establish patterns for prompt engineering, agent orchestration, and reusable AI‑driven workflows.
• Ensure generated code adheres to best practices in modularity, performance, and security.

System Architecture & Design

• Define backend, frontend, and data architectures for modern applications (web, SaaS, enterprise systems).
• Design APIs, data models, and workflows optimized for AI‑augmented systems.
• Integrate AI components (NLP, CV, predictive models) into production‑grade systems.

Engineering Governance

• Enforce code quality standards, version control discipline, testing strategies, and CI/CD pipelines.
• Review and refine AI‑generated code to meet production standards.
• Establish guardrails for reliability, observability, and maintainability.

Rapid Prototyping & Iteration

• Build functional prototypes at high velocity using AI tools.
• Iterate quickly based on stakeholder feedback and evolving requirements.
• Balance speed with long‑term scalability and technical debt management.

AI Strategy & Enablement

• Define how AI can be systematically leveraged across engineering workflows.
• Evaluate and integrate emerging AI tools and frameworks into the development stack.
• Drive adoption of AI‑native development practices across teams.

Leadership & Capability Building

Team Enablement

• Mentor engineers in adopting AI‑assisted development workflows effectively and responsibly.
• Conduct hands‑on sessions, code walkthroughs, and live builds to demonstrate best practices.
• Enable teams to move from ad‑hoc AI usage to structured, repeatable engineering approaches.

Upskilling & Knowledge Transfer

• Design internal playbooks, templates, and reusable patterns for AI‑driven development.
• Create documentation and training material to standardize practices across teams.
• Act as a multiplier—raising the overall productivity and capability of the engineering organization.

Technical Leadership

• Lead by example through high‑quality implementations and disciplined engineering practices.
• Influence architectural decisions and guide teams on trade‑offs between speed and scalability.
• Foster a culture of experimentation balanced with accountability and production readiness.

Required Qualifications

Experience

• 10+ years in AI / Machine Learning / Data Science or related domains.
• Recent, hands‑on experience building production software using AI‑assisted coding tools.
• Demonstrated track record of delivering real‑world products (not just prototypes).

Technical Expertise

• Strong proficiency in modern programming languages (e.g., JavaScript/TypeScript, Python, or similar).
• Experience with backend frameworks (Node.js, Express, FastAPI, etc.) and modern frontend stacks.
• Solid understanding of databases (SQL), APIs, and distributed systems.

AI Engineering Capability

• Deep familiarity with LLMs, prompt engineering, and agent‑based systems.
• Experience integrating AI models into applications (APIs, pipelines, inference systems).
• Understanding of AI limitations, evaluation, and reliability considerations.

Software Engineering Fundamentals

• Strong grasp of system design, scalability, and performance optimization.
• Experience with DevOps practices: CI/CD, containerization, cloud environments.
• Ability to write clean, maintainable, and testable code—even when AI‑generated.

Preferred Qualifications

• Experience building internal AI tooling, developer platforms, or automation systems.
• Familiarity with multi‑agent orchestration frameworks and workflow engines.
• Exposure to enterprise or government‑grade systems with high reliability requirements.
• Prior experience in mentoring teams or leading engineering initiatives.

Key Traits

• Builder & Leader: Ships products while uplifting the team.
• AI Fluent: Uses AI as a core engineering multiplier with discipline.
• Teacher Mindset: Actively shares knowledge and builds team capability.
• Systems Thinker: Understands end‑to‑end architecture and trade‑offs.
• Ownership Driven: Accountable for outcomes, not just outputs.

Success Criteria

• Deliver production‑ready systems at significantly accelerated timelines using AI.
• Establish and scale AI‑assisted development practices across teams.
• Measurably improve team productivity and engineering quality through upskilling.
• Create a self‑sustaining engineering culture that effectively leverages AI.

Contact

Interested candidates may contact: [e-mail]

WhatsApp: [phone]

Email: [e-mail]

Office Address (Head Quarters)

Plot No.14, Rajiv Gandhi Chandigarh Technology Park, Adjoining Infosys, Chandigarh, India – 160101

Office Address (Corporate Office)

Office No. 315, 3rd floor (Altrade) Platina Tower - 2 (Near Sikandarpur Metro station), Gurugram, Haryana, India - 122002