AI Engineering Manager/Lead at Intellectsoft-USA

, , India -

Full Time

Start Date

Immediate

Expiry Date

14 Apr, 26

Salary

0.0

Posted On

14 Jan, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Software Engineering, Technical Leadership, Backend Engineering, Python, FastAPI, Flask, GenAI, LLM, AI Solutions, Architecture, Delivery Management, Team Leadership, Collaboration, Engineering Standards, DevOps, Data Engineering

Industry

Software Development

Description

Our customer's product is an AI-powered platform that helps businesses make better decisions and work more efficiently. It uses advanced analytics and machine learning to analyze large amounts of data and provide useful insights and predictions. The platform is widely used in various industries, including healthcare, to optimize processes, improve customer experiences, and support innovation. It integrates easily with existing systems, making it easier for teams to make quick, data-driven decisions to deliver cutting-edge solutions. 8+ years of software engineering experience, including 3+ years in a technical leadership or engineering management role Strong backend engineering experience in Python (FastAPI, Flask, or similar frameworks) Hands-on experience building, integrating, and scaling GenAI / LLM-based systems, including prompt pipelines, model APIs, and agentic or workflow-based AI solutions Experience building and operating AI-enabled or data-intensive systems in production Proven ability to lead engineers while remaining technically credible Experience owning architecture and delivery across multiple services Comfortable operating in ambiguity and making pragmatic technical and delivery decisions Nice to have skills: Experience with cloud platforms (AWS, Azure, or GCP) Exposure to consulting or client-facing environments Background in platform, shared services, or accelerator-based engineering Responsibilities: Technical Leadership & Architecture: Own system-level architecture and technical decision-making across AI platforms and services Guide design and implementation of backend services, APIs, and AI integrations Ensure systems are scalable, secure, and production-ready Provide technical direction on GenAI workflows, agentic systems, and service orchestration Engineering Management & Team Leadership: Manage and mentor senior engineers, technical leads, and service owners Set clear expectations around ownership, quality, and delivery Support team growth through coaching, feedback, and development planning Build a culture of strong engineering fundamentals, accountability, and collaboration Delivery Ownership & Execution: Own delivery outcomes across multiple parallel workstreams Partner with product and delivery teams to plan, prioritize, and sequence work Identify risks early and make pragmatic trade-offs Act as escalation point for technical and delivery challenges AI Platform & Service Enablement: Oversee development of AI-powered backend services using Python (FastAPI / Flask) Enable GenAI use cases by integrating LLMs, prompt pipelines, agentic workflows, and enterprise data systems Drive standardization and reuse across AI components where appropriate Ensure clear service ownership and operational readiness Engineering Quality & Governance: Define and enforce engineering standards, patterns, and best practices Review designs and code at a system level to ensure quality and maintainability Identify technical debt and guide remediation plans Partner with DevOps to ensure observability, reliability, and operational clarity Cross-Functional Collaboration: Work closely with Product, AI/ML, DevOps, Data Engineering, and Consulting teams Translate business and client needs into sound technical approaches Communicate technical trade-offs clearly to non-technical stakeholders Support client-facing discussions when required for complex AI systems What Success Looks Like in This Role: Engineering teams operate independently with clear ownership GenAI systems are scalable, reliable, and reusable Delivery is predictable and high quality Technical decisions balance speed with long-term sustainability Engineers grow in capability, confidence, and impact Awesome projects with an impact Udemy courses of your choice Team-buildings, events, marathons & charity activities to connect and recharge Workshops, trainings, expert knowledge-sharing that keep you growing Clear career path Absence days for work-life balance Flexible hours & work setup - work from anywhere and organize your day your way

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Responsibilities

The AI Engineering Manager/Lead will own system-level architecture and technical decision-making across AI platforms and services while managing and mentoring engineering teams. They will ensure delivery outcomes across multiple workstreams and oversee the development of AI-powered backend services.