AI Engineer — Tech Lead (Only W2)

Role: AI Engineer — Tech Lead
Location: Remote
Interview Rounds: 3

Role Summary
We are seeking an experienced AI Engineer — Tech Lead to drive the design, development, and deployment of scalable AI, ML, and Generative AI solutions. This role combines deep technical expertise with strong leadership to build production-grade AI systems that deliver measurable business impact.

Key Responsibilities

• Lead end-to-end design and implementation of AI/ML and Generative AI solutions.
• Own AI system architecture, including model lifecycle, pipelines, and inference services.
• Review code, models, and architectures to ensure quality, scalability, performance, and security.
• Mentor, guide, and grow AI engineers and data scientists.
• Define and enforce engineering best practices and MLOps standards.
• Collaborate with cross-functional teams and stakeholders to align AI solutions with business needs.

AI & ML Engineering Responsibilities

• Design, train, fine-tune, and deploy ML, DL, and LLM-based models.
• Build and maintain pipelines for data ingestion, preprocessing, training, and evaluation.
• Implement prompt engineering, Retrieval-Augmented Generation (RAG) pipelines, and agentic workflows.
• Optimize models for accuracy, latency, and cost-effectiveness.

System Design & Architecture

• Architect cloud-native, scalable AI solutions.
• Integrate AI systems with enterprise platforms, APIs, and data sources.
• Ensure security, privacy, compliance, and governance requirements are met.

MLOps & Production Readiness

• Lead CI/CD processes for ML systems.
• Implement model versioning, monitoring, and drift detection.
• Drive observability, reliability, and operational excellence of AI services.

Basic Qualifications

• 12+ years of software engineering experience, with 7+ years focused on AI/ML.
• Proven experience in a Tech Lead or senior technical role.
• Strong Python programming skills.
• Experience with ML frameworks (PyTorch, TensorFlow, or Scikit-learn).
• Experience with cloud platforms (AWS, Azure, or Google Cloud Platform).

Preferred Qualifications (Nice to Have)

• Hands-on experience with Generative AI, LLMs, and agent-based systems.
• Knowledge of AI ethics, explainability, and bias mitigation.
• Master’s degree or higher in Computer Science, Artificial Intelligence, or a related field.

Soft Skills

• Strong technical leadership and ownership mindset.
• Excellent communication and stakeholder management skills.
• Passion for mentoring and team development.

Interview Process

• Three interview rounds (technical, architecture/leadership, and final/behavioural).