AIML Technical Lead

Job Title: Technical Lead AI/ML

Experience Level:

Job Summary

Senior/Lead AI/ML Engineer

ownership of solution delivery

Roles & Responsibilities

1. Model Development & Solution Ownership

• Lead the design, training, and optimization of AI/ML and Generative AI models.
• Build and oversee conversational AI solutions, chatbots, and agents using LangChain, RAG, and advanced prompting.
• Define architecture choices, trade-offs, and deployment strategies.
• Review and validate deliverables from junior engineers.
  

2. Data Handling & Strategy

• Oversee large-scale datasets for AI/ML applications, ensuring quality, transformation, and normalization.
• Define scalable and reliable data engineering workflows.
• Mentor junior team members in data preprocessing, feature engineering, and analysis.
  

3. Cloud AI/ML Deployment

• Lead deployment and optimization of AI/ML workflows on cloud platforms (preferably GCP: Vertex AI, BigQuery, Dataflow).
• Ensure

  production-grade scalability, observability, and retraining pipelines

  .
• Implement cost-efficient and secure deployment strategies.
  

4. Team Leadership & Mentoring

• Guide, mentor, and coach junior engineers in coding, debugging, and design reviews.
• Build a collaborative team environment that encourages learning and innovation.
• Provide technical direction, ensuring adherence to best practices and delivery timelines.
  

5. Stakeholder Collaboration

• Act as a bridge between business stakeholders and the technical team.
• Translate business requirements into technical roadmaps.
• Communicate risks, trade-offs, and progress clearly to leadership and clients.
  

6. Continuous Innovation

• Stay updated with the latest in Generative AI, LLMs, agent orchestration frameworks, and advanced ML techniques.
• Evaluate and adopt new technologies to enhance solutions.
• Proactively recommend improvements in architecture, processes, and delivery.
  

Required Skills & Qualifications

• 6+ years of experience in AI/ML solution development and deployment.
• Proven track record of

  end-to-end ownership of AI/ML projects

  .
• Strong programming skills in Python and SQL.
• Hands-on experience with

  Generative AI, LLMs, RAG, LangChain, MCP, and orchestration frameworks.

• Deep understanding of ML algorithms, statistical methods, and embeddings.
• Experience with

  cloud-native AI/ML workflows

  (Vertex AI, BigQuery, Dataflow, Cloud Functions).
• Strong grasp of

  MLOps pipelines

  : CI/CD, monitoring, and retraining workflows.
• Demonstrated experience mentoring and guiding junior engineers.
• Knowledge of Docker/Kubernetes for deployment and containerization.
  

Preferred Skills

• Familiarity with

  Reinforcement Learning from Human Feedback (RLHF)

  .
• Exposure to

  AI governance, compliance, and security best practices

  .
• Experience leading small-to-medium teams in delivery-focused environments.
• Knowledge of cost optimization strategies in cloud AI solutions.
• Hands-on with advanced agent frameworks (e.g., REACT, Agent-to-Agent orchestration).
  

Key Attributes

• Strong analytical, debugging, and problem-solving skills.
• Leadership, accountability, and ownership mindset.
  Ability to mentor and uplift junior engineers while meeting deadlines.
• Excellent communication skills with both technical and non-technical stakeholders.
• Proactive learner with the ability to adapt quickly to new technologies.