Principal AI & DevOps Engineer

BioLegend, Inc.; Maharashtra; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

BioLegend, Inc. seeks a seasoned technologist at the intersection of AI and business transformation.

You will own enterprise-scale AI initiatives, leading architecture assessment, and delivering production-grade AI-powered applications with Python backends and JS/Flutter frontends. Bring 8–12 years of full-stack experience, strong DevOps and IaC expertise, and a track record of driving tech strategy across business units.

Qualifications

• Bachelor's or Master's degree in Computer Science or equivalent field.
• 8–12 years of hands-on experience in full-stack development.
• Proven DevOps & Automation expertise with CI/CD tooling and IaC in production.

Responsibilities

• Lead strategic discovery and architectural assessment for AI-driven initiatives.
• Architect and deliver production-ready full-stack AI-powered applications using Python backends and JavaScript/Flutter frontends.
• Design and implement CI/CD pipelines for LLM-based applications and ensure robust testing.

Skills

Full-stack development

DevOps

IaC

Education

Bachelor's/Master's in CS

Job description

Are a seasoned technologist who thrives at the intersection of artificial intelligence and business transformation? Do you have a proven track record of turning complex AI/ML concepts into scalable, production-grade systems that move the needle for enterprise operations? If so, we want to hear from you.

What You'll Own

First 30 Days — Strategic Discovery & Architecture Assessment

• Enterprise Systems Audit: Rapidly assess our existing technical landscape, business architecture, and active AI workstreams — bringing your experience to quickly identify gaps, redundancies, and high-leverage opportunities others might miss.
• Cross-Functional Stakeholder Engagement: Lead structured discovery sessions across business units to surface operational friction points and define a prioritized roadmap for AI/ML intervention — drawing on your experience translating business pain into technical solutions.
• Technology Evaluation & Benchmarking: Apply your deep knowledge of emerging AI/ML technologies, industry trends, and software engineering best practices to evaluate our current toolchain and recommend improvements with clear rationale.
• Strategic Value Mapping: Deliver a well-reasoned assessment of where generative AI can reduce manual overhead, unlock creative capacity, or create competitive advantage — backed by your own experience doing exactly that.

Beyond 30 Days — Build, Lead, and Scale

• Full-Stack AI Application Development: Architect and deliver production-quality, full-stack AI-powered applications — leveraging Python backends and JavaScript/Flutter frontends — with a focus on performance, maintainability, and user experience informed by years of hands‑on delivery.
• Context Engineering & LLM Optimization: Design and implement sophisticated context engineering strategies — orchestrating enterprise data, memory systems, tool outputs, and prompt chaining within LLM context windows to produce accurate, structured, and reliable outputs at scale.
• End-to-End Pipeline Ownership: Own the full deployment lifecycle. Design, implement, and continuously improve CI/CD pipelines for LLM applications — including automated testing frameworks — applying best practices you've refined over your career.
• Data Engineering & ML Lifecycle Management: Drive data quality, pipeline integrity, and dataset governance to fuel deployed ML models — bringing mature engineering discipline to data validation, query optimization, and model input management.
• Observability & Performance Engineering: Establish robust monitoring frameworks using tools like AWS CloudWatch, define and track AI performance against business KPIs, and deliver executive‑ready dashboards and reports that connect system health to business outcomes.
• Technical Leadership & Knowledge Sharing: Mentor peers through code reviews, lead architectural discussions, and present fully operational solutions during stakeholder demos — translating complex AI/ML architecture into clear, compelling narratives for both technical and non-technical audiences.

Required Qualifications

• Bachelor's or Master's degree in Computer Science or equivalent field
• 8–12 years of hands‑on experience in full‑stack development
• Proven DevOps & Automation expertise: Deep experience with CI/CD tooling, deployment workflows, and Infrastructure as Code (IaC) in production environments

This role is designed for someone who brings their own perspective, methodology, and technical philosophy — not just executes a playbook. We value engineers who have strong opinions, loosely held, and the experience to back them up.