Tiger Analytics is seeking a highly experienced Lead AI Engineer to lead the end-to-end AI Engineering workstream for the Luma platform. This is a hands-on technical leadership role responsible for driving the architecture, design, and delivery of enterprise-scale Agentic AI solutions while serving as the primary technical interface for the client.
The ideal candidate will combine deep expertise in AI engineering, distributed systems, cloud-native architectures, and MLOps with exceptional stakeholder management skills. This individual will oversee multiple engineering pods, mentor technical teams, drive engineering excellence, and partner closely with client leadership to shape the AI roadmap and ensure successful delivery.
RequirementsKey Responsibilities
- Lead AI architecture and engineering roadmap for Agentic AI platforms.
- Design and deliver scalable, production-grade AI solutions.
- Oversee AI platform services, backend APIs, microservices, MLOps, observability, and cloud infrastructure.
- Partner with clients to translate business needs into AI solutions and lead architecture discussions.
- Mentor AI engineers, conduct design/code reviews, and drive engineering best practices.
- Lead multiple engineering teams, manage delivery, risks, and technical roadmaps.
- Evaluate and adopt emerging AI technologies and frameworks.
- AI/ML: GenAI, LLMs, Agentic AI, Multi-Agent Systems, RAG, Prompt Engineering, AI Guardrails, MLOps.
- Programming: Python (expert), Golang, REST APIs, Async Programming.
- Cloud: AWS (Bedrock/AgentCore preferred), Lambda, ECS/EKS, API Gateway, Step Functions, S3, DynamoDB, CloudWatch.
- Backend: Microservices, Docker, Kubernetes, Distributed Systems.
- Leadership: Client-facing consulting, architecture design, stakeholder management, mentoring, and technical leadership.
- 10–15+ years in software engineering with 5+ years leading AI/ML engineering teams.
- Experience building and deploying enterprise AI platforms on AWS.
- Strong client-facing, solution architecture, and cross-functional leadership experience.
- AWS Bedrock, LangGraph, CrewAI, AutoGen, AI Copilots, AI Observability, Enterprise SaaS, and large-scale distributed systems.
Benefits
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
Skills Required
- 10-15+ years in software engineering
- 5+ years leading AI/ML engineering teams
- Experience building and deploying enterprise AI platforms on AWS
- Python (expert)
- Golang
- GenAI
- LLMs
- Agentic AI
- Multi-Agent Systems
- RAG (Retrieval-Augmented Generation)
- Prompt Engineering
- AI Guardrails
- MLOps
- AWS (general)
- AWS Bedrock or AgentCore
- AWS Lambda
- ECS / EKS
- API Gateway
- Step Functions
- S3
- DynamoDB
- CloudWatch
- Microservices architecture
- Docker
- Kubernetes
- Distributed systems experience
- REST APIs
- Async programming
- Client-facing consulting and stakeholder management
- Mentoring, technical leadership, design and code reviews
- Experience overseeing multiple engineering teams/pods and managing delivery risks
- LangGraph
- CrewAI
- AutoGen
- AI Copilots
- AI Observability
- Enterprise SaaS experience
Tiger Analytics Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Tiger Analytics and has not been reviewed or approved by Tiger Analytics.
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Fair & Transparent Compensation — Feedback suggests pay is viewed as fair and market-aligned for many roles and geographies. Consistent, on-time pay and competitive packages in key markets reinforce a generally positive baseline.
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Healthcare Strength — Feedback suggests U.S. medical coverage is strong, with administration via a known benefits platform and plan options seen positively. Health insurance is often regarded as a bright spot within the package.
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Leave & Time Off Breadth — Feedback suggests generous PTO, paid sick days and holidays, and flexible PTO alongside remote-work options. These elements indicate broad time-off provisions available on paper.
Tiger Analytics Insights
What We Do
Tiger Analytics is a global leader in AI and Analytics, helping Fortune 1000 companies solve their toughest challenges. We offer fullstack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to shape a better tomorrow. Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore, and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. We are Great Place to Work-Certified™ and have been recognized by analyst firms such as Forrester, Gartner, Everest, ISG, HFS, and others. Ranked among the ‘Best’ and ‘Fastest Growing’ analytics firms lists by Inc., Financial Times, Economic Times and Analytics India Magazine. In India, our offices are located in Chennai, Hyderabad and Bangalore.
