Job description

Lead\Senior Lead- Data and AI (GenAI+App Eng)

Location: Chennai, Bengaluru, and Hyderabad

Who we are

Tiger Analytics is a global leader in AI and analytics, helping Fortune 1000 companies solve their toughest challenges. We offer full- stack 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. Many of our team leaders rank in Top 10 and 40 Under 40 lists, exemplifying our dedication to innovation and excellence.

We are a Great Place to Work-CertifiedTM (2022-26), recognized by analyst firms such as Forrester, Gartner, HFS, Everest, ISG and others. We have been ranked among the ‘Best’ and ‘Fastest Growing’ analytics firms lists by Inc., Financial Times, Economic Times and Analytics India Magazine

Curious about the role? What your typical day would look like?

We are seeking a highly technical and hands-on Lead/Senior Lead to champion our full-stack AI engineering and cognitive solutions. In this role, you will sit at the intersection of advanced generative AI application engineering, scalable system design, and enterprise-grade backend infrastructure.

You will be responsible for developing and deploying end-to-end Agentic AI systems, bringing both deep technical execution and robust cloud infrastructure solutioning to our clients.

As part of this role, you will:

Develop Agentic Systems: Build, integrate, and deploy autonomous, end-to-end Agentic AI systems and production-grade cognitive pipelines capable of solving complex corporate workflows.
Build Scalable Backend Solutions: Design and develop scalable backend applications and microservices-based architectures utilizing Python (or equivalent core backend technologies).
Implement Enterprise Design Patterns: Apply robust system design principles, microservices architectures, and software engineering design patterns to ensure high performance, security, and long-term maintainability.
Drive Cloud Infrastructure & Deployments: Build and deploy cloud-native applications tailored for scalability across modern cloud platforms (Azure, GCP, or AWS). Package applications utilizing containerization (Docker, Kubernetes) and leverage Infrastructure as Code (IaC) principles to provision cloud resources effectively.
Deliver Strategic Solutioning: Partner closely with data engineers, frontend developers, and architects to execute technical requirements, troubleshoot complex issues, and translate AI blueprints into production-ready software.
Ensure Engineering Quality: Participate in rigorous code and design reviews to ensure quality engineering, while providing technical guidance and mentorship to junior engineering teams.

Who do we expect?

Experience: 3+ to 8 years of technical backend engineering experience, with a heavy emphasis on system design, microservices, and API creation, alongside recent years dedicated to engineering GenAI solutions.
Core GenAI & Agentic Skills: Proven, hands-on experience building production-grade GenAI applications, LLM integrations, and engineering autonomous agentic solution applications for enterprise environments.
Backend Mastery: Elite software engineering skills in Python (or comparable backend technologies) with extensive experience building and consuming RESTful APIs, utilizing standard JSON data interchange, versioning, and robust exception handling.
System Design & Design Patterns: Strong expertise in application architecture, microservices, and a solid understanding of object-oriented/functional programming concepts and structural design patterns.
Cloud Architecture & Infrastructure: Solid knowledge of cloud architecture and hands-on experience deploying cloud-native applications on ecosystems such as Azure, GCP, or AWS. Must possess strong practical experience with containerization (Docker, Kubernetes) and Infrastructure as Code (IaC) principles (e.g., Terraform, CloudFormation).
Agile Mindset: Experience working fluidly within Agile development environments (such as Scrum or Kanban processes).

You are important to us, let’s stay connected!

Every individual comes with a different set of skills and qualities so even if you don’t tick all the boxes for the role today, we urge you

to apply as there might be a suitable/unique role for you tomorrow. We are an equal opportunity employer. Our diverse and inclusive

culture and values guide us to listen, trust, respect, and encourage people to grow the way they desire.

Note: The designation will be commensurate with expertise and experience. Compensation packages are among the best in the industry.

Mandatory Skills

generative ai,Python,Continuous Integration and Continuous Delivery

Role

As part of this role, you will:

Develop Agentic Systems: Build, integrate, and deploy autonomous, end-to-end Agentic AI systems and production-grade cognitive pipelines capable of solving complex corporate workflows.
Build Scalable Backend Solutions: Design and develop scalable backend applications and microservices-based architectures utilizing Python (or equivalent core backend technologies).
Implement Enterprise Design Patterns: Apply robust system design principles, microservices architectures, and software engineering design patterns to ensure high performance, security, and long-term maintainability.
Drive Cloud Infrastructure & Deployments: Build and deploy cloud-native applications tailored for scalability across modern cloud platforms (Azure, GCP, or AWS). Package applications utilizing containerization (Docker, Kubernetes) and leverage Infrastructure as Code (IaC) principles to provision cloud resources effectively.
Deliver Strategic Solutioning: Partner closely with data engineers, frontend developers, and architects to execute technical requirements, troubleshoot complex issues, and translate AI blueprints into production-ready software.
Ensure Engineering Quality: Participate in rigorous code and design reviews to ensure quality engineering, while providing technical guidance and mentorship to junior engineering teams.

Who do we expect?

Experience: 3+ to 8 years of technical backend engineering experience, with a heavy emphasis on system design, microservices, and API creation, alongside recent years dedicated to engineering GenAI solutions.
Core GenAI & Agentic Skills: Proven, hands-on experience building production-grade GenAI applications, LLM integrations, and engineering autonomous agentic solution applications for enterprise environments.
Backend Mastery: Elite software engineering skills in Python (or comparable backend technologies) with extensive experience building and consuming RESTful APIs, utilizing standard JSON data interchange, versioning, and robust exception handling.
System Design & Design Patterns: Strong expertise in application architecture, microservices, and a solid understanding of object-oriented/functional programming concepts and structural design patterns.
Cloud Architecture & Infrastructure: Solid knowledge of cloud architecture and hands-on experience deploying cloud-native applications on ecosystems such as Azure, GCP, or AWS. Must possess strong practical experience with containerization (Docker, Kubernetes) and Infrastructure as Code (IaC) principles (e.g., Terraform, CloudFormation).
Agile Mindset: Experience working fluidly within Agile development environments (such as Scrum or Kanban processes).

Education Qualification

B.Tech/B.E

Experience

5 to 8 years

Someone shared one job with you. ASAI keeps finding the rest.

Scored, not searched. Every role ranked against your actual profile.

Alerts as often as hourly. Reach new roles while the pile is still small.

Skill gaps, spelled out. See exactly which requirements you don't meet yet.

Verified jobs, only. Say no to ghost jobs. Your time deserves respect.

Someone shared one job with you. ASAI keeps finding the rest.

Scored, not searched. Every role ranked against your actual profile.

Alerts as often as hourly. Reach new roles while the pile is still small.

Skill gaps, spelled out. See exactly which requirements you don't meet yet.

Verified jobs, only. Say no to ghost jobs. Your time deserves respect.

Job description

Lead\Senior Lead- Data and AI (GenAI+App Eng)

Location: Chennai, Bengaluru, and Hyderabad

Who we are

Curious about the role? What your typical day would look like?

You will be responsible for developing and deploying end-to-end Agentic AI systems, bringing both deep technical execution and robust cloud infrastructure solutioning to our clients.

As part of this role, you will:

Develop Agentic Systems: Build, integrate, and deploy autonomous, end-to-end Agentic AI systems and production-grade cognitive pipelines capable of solving complex corporate workflows.
Build Scalable Backend Solutions: Design and develop scalable backend applications and microservices-based architectures utilizing Python (or equivalent core backend technologies).
Implement Enterprise Design Patterns: Apply robust system design principles, microservices architectures, and software engineering design patterns to ensure high performance, security, and long-term maintainability.
Drive Cloud Infrastructure & Deployments: Build and deploy cloud-native applications tailored for scalability across modern cloud platforms (Azure, GCP, or AWS). Package applications utilizing containerization (Docker, Kubernetes) and leverage Infrastructure as Code (IaC) principles to provision cloud resources effectively.
Deliver Strategic Solutioning: Partner closely with data engineers, frontend developers, and architects to execute technical requirements, troubleshoot complex issues, and translate AI blueprints into production-ready software.
Ensure Engineering Quality: Participate in rigorous code and design reviews to ensure quality engineering, while providing technical guidance and mentorship to junior engineering teams.

Who do we expect?

Experience: 3+ to 8 years of technical backend engineering experience, with a heavy emphasis on system design, microservices, and API creation, alongside recent years dedicated to engineering GenAI solutions.
Core GenAI & Agentic Skills: Proven, hands-on experience building production-grade GenAI applications, LLM integrations, and engineering autonomous agentic solution applications for enterprise environments.
Backend Mastery: Elite software engineering skills in Python (or comparable backend technologies) with extensive experience building and consuming RESTful APIs, utilizing standard JSON data interchange, versioning, and robust exception handling.
System Design & Design Patterns: Strong expertise in application architecture, microservices, and a solid understanding of object-oriented/functional programming concepts and structural design patterns.
Cloud Architecture & Infrastructure: Solid knowledge of cloud architecture and hands-on experience deploying cloud-native applications on ecosystems such as Azure, GCP, or AWS. Must possess strong practical experience with containerization (Docker, Kubernetes) and Infrastructure as Code (IaC) principles (e.g., Terraform, CloudFormation).
Agile Mindset: Experience working fluidly within Agile development environments (such as Scrum or Kanban processes).

You are important to us, let’s stay connected!

Every individual comes with a different set of skills and qualities so even if you don’t tick all the boxes for the role today, we urge you

to apply as there might be a suitable/unique role for you tomorrow. We are an equal opportunity employer. Our diverse and inclusive

culture and values guide us to listen, trust, respect, and encourage people to grow the way they desire.

Note: The designation will be commensurate with expertise and experience. Compensation packages are among the best in the industry.

Mandatory Skills

generative ai,Python,Continuous Integration and Continuous Delivery

Role

As part of this role, you will:

Develop Agentic Systems: Build, integrate, and deploy autonomous, end-to-end Agentic AI systems and production-grade cognitive pipelines capable of solving complex corporate workflows.
Build Scalable Backend Solutions: Design and develop scalable backend applications and microservices-based architectures utilizing Python (or equivalent core backend technologies).
Implement Enterprise Design Patterns: Apply robust system design principles, microservices architectures, and software engineering design patterns to ensure high performance, security, and long-term maintainability.
Drive Cloud Infrastructure & Deployments: Build and deploy cloud-native applications tailored for scalability across modern cloud platforms (Azure, GCP, or AWS). Package applications utilizing containerization (Docker, Kubernetes) and leverage Infrastructure as Code (IaC) principles to provision cloud resources effectively.
Deliver Strategic Solutioning: Partner closely with data engineers, frontend developers, and architects to execute technical requirements, troubleshoot complex issues, and translate AI blueprints into production-ready software.
Ensure Engineering Quality: Participate in rigorous code and design reviews to ensure quality engineering, while providing technical guidance and mentorship to junior engineering teams.

Who do we expect?

Experience: 3+ to 8 years of technical backend engineering experience, with a heavy emphasis on system design, microservices, and API creation, alongside recent years dedicated to engineering GenAI solutions.
Core GenAI & Agentic Skills: Proven, hands-on experience building production-grade GenAI applications, LLM integrations, and engineering autonomous agentic solution applications for enterprise environments.
Backend Mastery: Elite software engineering skills in Python (or comparable backend technologies) with extensive experience building and consuming RESTful APIs, utilizing standard JSON data interchange, versioning, and robust exception handling.
System Design & Design Patterns: Strong expertise in application architecture, microservices, and a solid understanding of object-oriented/functional programming concepts and structural design patterns.
Cloud Architecture & Infrastructure: Solid knowledge of cloud architecture and hands-on experience deploying cloud-native applications on ecosystems such as Azure, GCP, or AWS. Must possess strong practical experience with containerization (Docker, Kubernetes) and Infrastructure as Code (IaC) principles (e.g., Terraform, CloudFormation).
Agile Mindset: Experience working fluidly within Agile development environments (such as Scrum or Kanban processes).