4+ Serverless Jobs in Chennai | Serverless Job openings in Chennai

Role overview:

We are hiring one Senior Backend Engineer to take end-to-end ownership of our serverless backend — a hands-on IC role for someone both technically excellent and comfortable being one of the few people the entire backend depends on. You'll own the services across several Node.js and Python repositories, work directly with the founders and product team, and set the technical bar for reliability, security, and performance.

Key responsibilities

• Design, build, and operate AWS Lambda services across our HCM/workforce, project-management, commercial/revenue, permissions, and document domains — each comprising dozens of functions.
• Own the multi-tenant PostgreSQL data layer — schema design, query performance, and the permission/relationship model — end to end.
• Maintain and evolve the request path — API Gateway → custom Lambda authorizer → VPC-bound Lambda → private databases — including the runtime IAM/credential model that scopes every request.
• Safeguard tenant isolation and security across a per-company Cognito authentication model.
• Build and maintain integrations with external construction data environments (Asite, Autodesk Construction Cloud), including large-scale document synchronization.
• Optimize performance and reliability to keep latency-sensitive endpoints well within platform limits under growing load.
• Raise the engineering bar — testing, observability, CI/CD, and modernization of legacy components.
• Debug and resolve production incidents to root cause, and put safeguards in place so they don't recur.
• Document decisions and designs and collaborate with the frontend (Angular) and product teams.

Challenges you'll solve.

We prefer to be candid — these are the problems that make this role genuinely interesting:

Latency under a hard ceiling

API Gateway terminates any request beyond ~29 seconds regardless of the Lambda's own timeout — yet much of our value comes from heavy cross-project reporting. You'll keep p95 latency within budget through set-based SQL, pagination, streaming, and asynchronous processing.

Least-privilege, per-request security

A shared custom authorizer mints short-lived, request-scoped credentials via sts:AssumeRole under a strict 2,048-character inline session-policy limit. You'll design permission models that stay within that budget and reason about IAM precisely.

Graph-shaped data, relational store

The permission and relationship model is inherently graph-like, but lives in PostgreSQL — you'll model it with recursive queries, careful indexing, and set-based traversal rather than reaching for a separate graph engine.

Watertight multi-tenancy

One Cognito pool per company and tenant-scoped access throughout — isolation is a first-order concern.

VPC-bound serverless

Lambdas run inside a VPC to reach private databases; you'll manage cold starts, connection lifecycles, and pool limits.

Resilient external integrations

Syncing large document sets from third-party APIs (including SOAP/XML) demands backpressure, deduplication, retries, and graceful partial-failure handling.

Compute-heavy workloads

Server-side PDF generation, image processing, and multi-currency handling within Lambda's memory and time constraints.

The stack.

Runtime — Node.js, Python, AWS Lambda

AWS services — -1 API Gateway, Lambda, Cognito, STS / IAM, Secrets Manager, S3 CloudWatch, VPC, EC2

Infrastructure & CI/CD- AWS SAM, CodePipeline → CodeBuild Shared Data —PostgreSQL

Qualifications.

• 5+ years building and operating production backend systems.
• Deep expertise in Node.js and JavaScript — the asynchronous model, event loop, and memory behavior — plus solid working proficiency in Python and its production behavior.
• Strong hands-on AWS experience, ideally serverless (Lambda, API Gateway, IAM/STS, VPC, Secrets Manager, CloudWatch) — able to reason about IAM policies, not just apply them.
• Advanced SQL and relational data modeling — set-based query design and a working understanding of why N+1 patterns cause production issues.
• Proven production-debugging ability — root-cause analysis in distributed systems from logs and first principles.
• Strong ownership, sound judgment, and clear written communication — able to make good decisions with incomplete information and explain trade-offs to non-engineers.

Interview Process:

Introductory call-Mutual fit and role overview.

Technical deep-dive- A walkthrough of a challenging production problem you have owned.

Practical exercise -A realistic backend task, or a walkthrough of your own representative code.

System design- Collaborative design on a real scenario.

Final conversation- Values, ownership, compensation, and offer.

• Bachelors in Computer Science, Information Systems or equivalent.
• 6 years experience delivering highly available web/mobile applications including 1-3 years as Senior/Lead developer.
• Prior experience in retail domain is a plus.
• 3 years of experience working with distributed teams.
• Deep knowledge of UI Libraries / Frameworks, API (REST), API Management and building scalable and high performance Web APIs.
• Must have experience building websites using Javascript and Java technologies (e.g. Typescript, Spring Boot etc.). Search Engine and Native App development experience is a plus.
• AWS Serverless Cloud native services experience with Lambda functions, SNS, SQS, DynamoDB, API Gateway etc.
• Strong knowledge of Caching frameworks, data structures, algorithms, operating systems, and distributed systems.
• Strong understanding of databases, NoSQL data stores, storage and distributed persistence technologies.
• Strong communication and presentation skills.
• Passionate about enabling next generation experiences.
• Experience with automated testing, deployment pipelines and cloud based infrastructure

• Develop omni-channel digital solutions leveraging serverless and micro services in a cloud based platform to develop backend services.
• Design high/low level solutions, contribute towards architecture and technical roadmap.
• Lead technical implementation/delivery.
• Host/Lead technical discussions.
• Champion software development best practices, test driven development, CI and CD.
• Build cloud native and highly cost efficient solutions.
• Innovate, Unlearn and Disrupt. Research next generation frameworks and technologies.
• Embrace change. 

We are looking for an outstanding ML Architect (Deployments) with expertise in deploying Machine Learning solutions/models into production and scaling them to serve millions of customers. A candidate with an adaptable and productive working style which fits in a fast-moving environment.

Skills:

- 5+ years deploying Machine Learning pipelines in large enterprise production systems.

- Experience developing end to end ML solutions from business hypothesis to deployment / understanding the entirety of the ML development life cycle.
- Expert in modern software development practices; solid experience using source control management (CI/CD).
- Proficient in designing relevant architecture / microservices to fulfil application integration, model monitoring, training / re-training, model management, model deployment, model experimentation/development, alert mechanisms.
- Experience with public cloud platforms (Azure, AWS, GCP).
- Serverless services like lambda, azure functions, and/or cloud functions.
- Orchestration services like data factory, data pipeline, and/or data flow.
- Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform.
- Data warehouse services like snowflake, redshift, bigquery, azure sql dw, AWS Redshift.
- Distributed computing services like Pyspark, EMR, Databricks.
- Data storage services like cloud storage, S3, blob, S3 Glacier.
- Data visualization tools like Power BI, Tableau, Quicksight, and/or Qlik.
- Proven experience serving up predictive algorithms and analytics through batch and real-time APIs.
- Solid working experience with software engineers, data scientists, product owners, business analysts, project managers, and business stakeholders to design the holistic solution.
- Strong technical acumen around automated testing.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Strong hands-on experience with statistical packages and ML libraries (e.g., Python scikit learn, Spark MLlib, etc.)
- Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.)
- Experience in developing and debugging in one or more of the languages Java, Python.
- Ability to work in cross functional teams.
- Apply Machine Learning techniques in production including, but not limited to, neuralnets, regression, decision trees, random forests, ensembles, SVM, Bayesian models, K-Means, etc.

Roles and Responsibilities:

Deploying ML models into production, and scaling them to serve millions of customers.

Technical solutioning skills with deep understanding of technical API integrations, AI / Data Science, BigData and public cloud architectures / deployments in a SaaS environment.

Strong stakeholder relationship management skills - able to influence and manage the expectations of senior executives.
Strong networking skills with the ability to build and maintain strong relationships with both business, operations and technology teams internally and externally.

Provide software design and programming support to projects.

 Qualifications & Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Machine Learning Architect (Deployments) or a similar role for 5-7 years.