Role & responsibilities

- Lead, mentor, and upskill a team of junior and mid-level developers
- Drive end-to-end ownership of AI/ML solution design, architecture, and delivery
- Design, develop, and deploy scalable AI/ML-based solutions using Python
- Define and enforce system architecture, coding standards, and best practices
- Write clean, efficient, and production-ready Python code
- Develop automation, web extraction, scripting, and integration workflows
- Conduct code reviews and ensure high-quality engineering output
- Collaborate with stakeholders to translate business needs into technical solutions
- Ensure scalability, performance, and security of AI systems
- Stay updated with emerging AI technologies, tools, and frameworks
- Drive innovation and continuous improvement across projects and teams

Preferred candidate profile

- 8-13 years of overall experience in software development
- 4-5 years of hands-on Python development experience
- 3 4 years of team leadership / mentoring experience
- Proven experience building and deploying AI/ML solutions in production
- Experience in Data Science (data analysis, modeling, evaluation)
- Advanced problem-solving and system design capabilities
- Deep understanding of AI system architecture, including:



o Model architecture o Prompt engineering o System layers and integrations o End-to-end solution design
- Ability to architect scalable, reliable, and production-grade systems
- Solid technical decision-making and leadership skills
- Proven experience working with or graduating from top-tier universities or reputed organizations
- Strong communication and stakeholder management skills
- Ability to align technical solutions with business objectives Preferred Skills
- Advanced expertise in Python frameworks and AI/ML libraries
- Experience with LLMs, Generative AI, or agentic AI systems
- Experience working on multiple large-scale AI/ML projects
- Exposure to cloud platforms (AWS, Azure, GCP)
- Knowledge of MLOps, CI/CD pipelines, and containerization (Docker, Kubernetes)
- Experience with modern AI tooling and pipelines Key Performance Indicators (KPIs)
- Successful delivery of AI/ML projects within defined timelines
- Code quality and adherence to architectural standards
- System scalability, reliability, and performance optimization
- Team development, mentorship impact, and retention
- Innovation and adoption of emerging AI technologies

📌 Technical Project Manager (Ahmedabad)
🏢 infoAnalytica
📍 Ahmedabad