AI Technical Lead

About the Role

AI Technical Lead

Responsibilities

• Architecture & Strategy:

  Define and evolve the technical architecture of a multi-tenant SaaS platform.

• Engineering Leadership:

  Translate product requirements into robust, scalable technical solutions across APIs, microservices, and automation frameworks.

• Team Leadership:

  Mentor and guide engineers, establish coding standards, and foster a culture of technical excellence.

• AI & Data Systems

  : Oversee design of ML/AI-driven modules, analytics engines, and data pipelines.

• Agentic AI Solutions:

  Design and implement autonomous and semi-autonomous AI agents to drive decision-making, workflow automation, and user interactions.

• LLM Integration & Orchestration:

  Lead initiatives in leveraging large language models (LLMs), multi-agent orchestration frameworks, and vector databases to create adaptive, intelligent systems.

• Integration Ecosystem:

  Lead development of integrations with third-party systems (eCommerce platforms, ERPs, CRMs, marketplaces, etc.).

• Security & Compliance:

  Ensure platform adheres to enterprise-grade security, compliance, and privacy standards.

• Performance & Scalability:

  Anticipate growth needs and ensure high availability, reliability, and cost optimization.

• Cross-Functional Collaboration:

  Partner with product, design, and business stakeholders to align technical execution with business goals.

Qualifications

• 10–15 years of experience in software engineering with at least 5 years in technical leadership roles.
• Proven track record of architecting and scaling SaaS platforms.
• Strong expertise in cloud-native development (AWS, Azure, or GCP), microservices, and API-first architectures.
• Hands-on experience with modern backend frameworks (Node.js, Python, Java, or Go).
• Background in data engineering, event-driven systems, and ML/AI integration.
• Experience designing AI/ML solutions for personalization, forecasting, NLP, and anomaly detection.
• Demonstrated experience with agentic AI systems (multi-agent orchestration, task planning, tool-use frameworks).
• Strong knowledge of DevSecOps, CI/CD, MLOps, and infrastructure-as-code practices.
• Demonstrated success in building and leading high-performing engineering teams.

Preferred Skills

• Experience in SaaS, eCommerce, or AI/ML-driven products.
• Knowledge of ERP, CRM, or marketplace integrations.
• Familiarity with big data frameworks (Kafka, Spark, Snowflake, etc.).
• Experience with modern AI/ML toolchains (TensorFlow, PyTorch, Hugging Face, LangChain, vector databases).
• Exposure to observability and monitoring tools (Grafana, Prometheus, Datadog, ML model monitoring platforms).
• Experience in early-stage/startup environments with fast-paced execution.