Platform Engineer

Role overview

The client is building a multimodal AI platform that processes multi-hour video, audio and text to generate structured insights, narratives and highlight workflows for broadcasters and media organisations.

We are seeking a Backend / Platform Engineer to design and build high-throughput media pipelines, robust APIs, and model-serving infrastructure that connect our AI engine (video perception + multimodal reasoning) to real products and customer environments.

This is not a CRUD‑only backend role.

You will work on:

• long‑running jobs
• distributed processing
• GPU inference orchestration
• storage for embeddings and metadata
• integration with AI models
• reliability and observability at scale

Key responsibilities

Media ingestion & processing pipelines

• Design and implement ingestion pipelines for multi‑hour video and audio content.
• Build microservices for frame extraction, audio processing, transcription integration and metadata generation.
• Handle long‑running, asynchronous jobs using queues, workers and robust retry strategies.
• Integrate with FFmpeg or similar tools for transcoding, segmenting and preparing media for AI models.

API & platform architecture

• Design and implement REST/gRPC APIs that expose AI model outputs (perception, multimodal alignment, narratives) to frontend and external systems.
• Define clear contracts for internal services and external integrations.
• Implement authentication, authorisation and rate‑limiting for platform endpoints.
• Ensure backward‑compatible API evolution as the product matures.

Model‑serving & AI integration

• Integrate with AI inference services (video models, multimodal models, LLM/VLM) running on GPUs or specialised infrastructure.
• Design request/response flows that handle large payloads, streaming outputs and structured results.
• Optimise throughput and latency for inference pipelines, including batching, caching and concurrency control.
• Collaborate closely with AI engineers to productionise models and debug end‑to‑end behaviour.

Storage, data models & performance

• Design data models to store embeddings, timelines, metadata, scene/shot boundaries, and narrative units.
• Work with appropriate storage technologies (SQL/NoSQL, object storage, search indices) based on access patterns.
• Implement indexing and query strategies for fast retrieval of segments, highlights and multimodal insights.
• Optimise performance for large datasets and high‑volume workloads.

Reliability, observability & operations

• Implement logging, metrics and tracing across services for debugging and monitoring.
• Set up health checks, circuit breakers and graceful degradation for critical services.
• Work with CI/CD pipelines to ensure safe, repeatable deployments.
• Collaborate on Kubernetes‑based deployments (or equivalent orchestration) for scaling services.

Requirements (must‑have)

Experience:

• 4–8 years in backend or platform engineering.
• At least 3 years working on distributed systems, high‑throughput services or complex pipelines (not just simple CRUD apps).

Languages & frameworks:

• Strong proficiency in Python or Node.js (one primary, both are a plus).
• Experience with at least one modern backend framework (FastAPI, Flask, Express, NestJS, etc.).

Distributed systems & pipelines:

• Hands‑on experience with queues and workers (e.g. Celery, RabbitMQ, Kafka, SQS, etc.).
• Experience building asynchronous, long‑running job pipelines.
• Understanding of idempotency, retries, backoff, and failure handling.

APIs & integration:

• Strong experience designing and implementing REST APIs (gRPC is a plus).
• Experience integrating with external services and handling network‑level failures.

Cloud & infrastructure:

• Experience deploying services on AWS, GCP or Azure (EC2/Compute Engine, S3/GCS, IAM, networking basics).
• Experience with Docker; exposure to Kubernetes is a strong plus.

Data & storage:

• Experience with SQL and at least one NoSQL store.
• Ability to design schemas and data models for performance and maintainability.

Engineering quality:

• Strong debugging skills across services and environments.
• Experience with unit/integration tests for backend systems.
• Clear, structured communication in English.

Nice‑to‑have

• Experience with media/video processing (FFmpeg, transcoding, segmenting).
• Experience with AI/ML model integration (serving models, handling inference requests).
• Experience with search/retrieval systems (e.g. Elasticsearch, vector databases).
• Experience with observability stacks (Prometheus, Grafana, OpenTelemetry).
• Experience working with remote teams across time zones.

What we are explicitly NOT looking for

To reduce noise and mismatches, we are not looking for:

• Pure CRUD‑only backend developers with no pipeline or distributed systems experience.
• Engineers who have only worked on small, single‑service apps without scale or complexity.
• Candidates who cannot explain trade‑offs in architecture, data modelling and reliability.
• Candidates who are uncomfortable with ownership of subsystems end‑to‑end.

Why join us

• Work on real, complex problems at the intersection of media, AI and distributed systems.
• Collaborate with senior AI engineers working on perception, multimodal fusion and narrative reasoning.
• Build the core platform that turns AI models into a usable product for broadcasters and media organisations.
• Operate with high ownership, clear expectations and direct access to the CTO.

Job Title: Platform Engineer

Location: Bangalore(Onsite)

Experience Level: 3-8

Salary Range: 20-30LPA

Description:

Join a team building an AI-native enterprise platform that helps businesses make faster, smarter and more consistent operational decisions using AI, enterprise data and workflow automation.

Design and build the core platform for enterprise decision workflows. Develop reusable workflow and decision runtimes. Build scalable, cloud-native distributed systems and event-driven architectures. Design enterprise-grade APIs and platform services. Build integrations with systems such as SAP and Oracle. Develop secure multi-tenant services with authentication and RBAC. Build and manage AWS cloud infrastructure and deployment systems. Implement monitoring and observability for production systems. Support both cloud and on-premise deployments. Enable faster onboarding and deployment of new enterprise workflows.

Requirements:

- Strong hands-on experience with Python

- FastAPI

- PostgreSQL

- Docker

- AWS

- Practical experience with Redis

- Kafka/event streaming

- REST APIs

- CI/CD

- Git

- Good understanding of Kubernetes

- Distributed systems

- Event-driven architecture

- Enterprise SaaS

- Microservices

- Strong backend engineering fundamentals

- Ability to design scalable, reliable and production-ready systems

Strong Python Developer profile with robust AWS exposure

2

Mandatory (Experience 1): Must have 7+ years of hands-on software development experience with at least the recent 4+ years in Python and strong hands on knowledge of AWS

3

Mandatory (Tech skill 1): Must have strong working knowledge of Python.

4

Mandatory (Tech skill 2): Must have good understanding of AWS services including EC2, S3, Lambda, IAM, CloudWatch, and ECS or ECR

5

Mandatory (Tech skill 3): Must be able to write and understand REST APIs

6

Mandatory (Tech skill 4): Must be comfortable with version control tools such as Git, GitHub, Bitbucket, or GitLab

7

Mandatory (Tech skill 5): Must have good understanding of databases such as PostgreSQL, MySQL, or DynamoDB

8

Mandatory (Tech skill 6): Must have familiarity with Linux commands and shell scripting

9

Mandatory (Skill): Must have good debugging and problem-solving skills, with the ability to read existing code and make changes independently with light guidance

10

Mandatory (Skill 2): Must have strong communication skills

11

Preferred (Tech skill 1): Experience with AWS CodeCommit, and exposure to AWS CodeBuild, CodeDeploy, CodePipeline, GitHub Actions, Jenkins, or similar CI/CD tools

12

Preferred (Tech skill 2): Basic understanding of CI/CD pipelines

13

Preferred (Tech skill 3): Experience with Docker or container-based applications

14

Preferred (Tech skill 4): Basic knowledge of infrastructure-as-code tools such as Terraform or AWS CloudFormation

We are seeking a Senior Full Stack Engineer to join our team in a long-term contractor capacity to continue development of a production-grade platform hosted on AWS.

This application supports policy processing, third-party integrations, compliance workflows, reporting, and intelligent automation capabilities. The ideal candidate is a strong software engineer first, capable of contributing across the full stack while helping scale and evolve the platform.

This role requires someone who can step into an existing system, understand complex workflows quickly, and independently deliver high-quality solutions.

Responsibilities

• Design, develop, and maintain full-stack application features across frontend and backend systems

• Build and support integrations with third-party systems and APIs

• Develop workflow-driven processes using Temporal

• Build scalable APIs and backend services using Python

• Maintain and optimize relational databases using PostgreSQL

• Develop reporting and analytics capabilities using charting libraries

• Contribute to AI-enabled features and integrations within the platform

• Improve CI/CD pipelines and deployment processes

• Participate in architecture discussions and help shape long-term technical direction

• Work closely with business and technical stakeholders to deliver production-ready solutions

Required Qualifications

Engineering

• at least 7+ years of full stack software engineering experience

• Strong proficiency in Python

• Strong frontend development experience with modern web frameworks

• Strong backend API development experience

• Experience designing and building scalable applications

• Strong understanding of software architecture and best practices

• Experience working in complex, integrated systems

Workflow and Orchestration

• Proven experience with Temporal

• Experience building and managing workflow orchestration patterns

• Familiarity with asynchronous processing and event-driven systems

Database and Reporting

• Strong experience with PostgreSQL

• Strong SQL and data modeling experience

• Experience building reporting dashboards and analytics features

• Experience with charting libraries such as Chart.js, D3.js, or Plotly

DevOps

• Experience with CI/CD pipelines

• Familiarity with containerized deployments

• Experience with cloud environments and modern development workflows

Preferred Qualifications

• Experience in insurance, surplus lines, or compliance-based applications

• Experience integrating with third-party vendors and external APIs

• Experience with AI tooling, LLM integrations, and context engineering

• Experience building intelligent automation features

What We Are Looking For

• Self-driven and highly autonomous

• Strong problem-solving ability

• Comfortable with ownership and accountability

• Able to contribute with minimal supervision

• Strong communication skills in English

• Comfortable working U.S.-based business hours

Ideal Candidate

A senior full stack engineer who can quickly contribute to an active production system, own features end-to-end, and help expand a platform that sits at the center of complex business workflows and integrations. Send resume with projects and contact information.

Full-Stack Engineer (Backend Heavy)

Experience: 4–6 Years | Function: Engineering — Product | Location: On-site

About Us

We’re building the next generation of AI-powered business software, and we’re looking for people who want to shape that future with us. With Lumen, we’re reimagining how users interact with CRM — moving beyond screens, menus and dashboards to an intelligent interface where users can simply ask AI to take actions, retrieve knowledge, generate insights and get work done. With Agent Studio, we’re enabling businesses to build, test and deploy their own AI agents for real-world workflows. And with Invorto, we’re bringing AI to voice, allowing businesses to create intelligent voice agents tailored to their customer and operational use cases.

What makes this especially exciting is the stage and scale of the opportunity. You’ll get to work on genuinely hard problems across LLMs, agents, reasoning, orchestration, voice AI, evaluation, reliability and enterprise security — not as isolated experiments, but as products used in real business workflows. You’ll have the opportunity to build zero-to-one, own meaningful parts of the product end-to-end, work closely with customers, experiment rapidly, and see your work reach production at scale.

Why join now? Because the playbook for enterprise AI is still being written. You won’t just be implementing someone else’s roadmap — you’ll help define the product, architecture and experiences that become that playbook. Expect high ownership, fast iteration, hard technical and product problems, direct customer impact, and the chance to build AI systems that have to work reliably in the real world — not just in a demo.

About the Role

We are looking for a Full-Stack Engineer with a strong backend bias to help build end-to-end product experiences across Lumen and Agent Studio. You will own features from database and API design through to the front-end experience, working closely with product and design to ship AI-powered experiences that real business users depend on every day.

What You’ll Do

Design and build backend services and APIs in Python that power core product and AI-agent features.

Build front-end interfaces and experiences that let users interact naturally with AI agents, insights and CRM workflows.

Own features end-to-end — from data modeling and backend logic to UI implementation, testing and release.

Work with product managers and designers to translate requirements into well-architected, scalable systems.

Integrate with LLM-based and agentic backend systems built by the AI/ML engineering team.

Optimize application performance, reliability and code quality across the stack.

Engage directly with customers and customer success teams to understand workflows, triage issues and inform roadmap decisions.

What We’re Looking For

4–6 years of professional full-stack engineering experience, with a clear backend-heavy skill set in Python.

Strong experience designing and building REST/GraphQL APIs, data models and scalable backend services.

Working proficiency with modern front-end frameworks (e.g., React) to build and integrate user-facing features.

Experience with relational/NoSQL databases, caching and cloud infrastructure.

Ability to move fast in a zero-to-one environment while maintaining code quality and system reliability.

Strong communication skills — this is a customer-facing role, and you will be expected to clearly articulate technical concepts, decisions and trade-offs to both technical and non-technical stakeholders, including customers.

Good to Have

Experience building features on top of LLM or AI-agent backends.

Prior experience in CRM, SaaS or enterprise business applications.

Exposure to real-time or voice-based product interfaces.

Amura’s Vision 

We believe that the most under-appreciated route to releasing untapped human potential is to build a healthier body, and through which a better brain. This allows us to do more of everything that is important to each one of us.

Billions of healthier brains, sitting in healthier bodies, can take up more complex problems that defy solutions today, including many existential threats, and solve them in just a few decades.

Billions of healthier brains will make the world richer beyond what we can imagine today. The surplus wealth, combined with better human capabilities, will lead us to a new renaissance, giving us a richer and more beautiful culture.

These healthier brains will be equipped with deeper intellect, be less acrimonious, more magnanimous, and have a kinder outlook on the world, resulting in a world that is better than any previous time.

We find this vision of the future exhilarating. Our hopes and dreams are to create this future as quickly as possible and ensure that it is widely distributed and optimized to maximize all forms of human excellence. 

Role Overview 

We are looking for a highly skilled Senior DevOps Engineer (AI-Native Infrastructure & Platform Engineering) with deep expertise in AWS cloud infrastructure, automation, AI infrastructure operations, and modern DevOps/SRE practices.

This role goes beyond traditional DevOps and requires a seasoned specialist capable of building and operating AI-ready infrastructure platforms that support high-throughput APIs, LLM/AI workloads, GPU-based compute, data-intensive systems, real-time inference pipelines, and scalable ML platforms.

You will be responsible for architecting, automating, securing, and optimizing highly scalable and cost-efficient cloud environments that enable high-velocity engineering and AI teams. This is an ideal position for someone who combines technical ownership, an automation-first mindset, and a passion for developer productivity and platform reliability. 

Key Responsibilities 

Cloud Infrastructure & Platform Engineering (AWS) 

• Architect, deploy, and manage highly scalable and secure infrastructure on AWS. Design cloud platforms supporting AI/ML workloads, data pipelines, real-time APIs, and high-concurrency backend systems.
• Hands-on expertise with key AWS services including EC2, ECS/EKS, Lambda, RDS, DynamoDB, S3, VPC, CloudFront, IAM, CloudWatch, and GPU-enabled instances.
• Build and maintain Infrastructure-as-Code (IaC) using Terraform, CloudFormation, or AWS CDK.
• Design multi-AZ and multi-region architectures for high availability and disaster recovery (HA/DR).
• Build reusable platform templates and shared infrastructure modules. 

AI/ML Infrastructure & MLOps 

• Build and maintain infrastructure for LLM applications, AI inference workloads, model serving platforms, vector databases, and feature stores.
• Support GPU-based workloads and optimize compute/storage usage.
• Enable scalable deployment patterns for AI applications using Kubernetes/EKS. Collaborate with Data Science and ML Engineering teams on model deployment, training/tuning of models, CI/CD for ML systems, experiment environments, and reproducibility.
• Support orchestration and deployment of AI workflows and inference services while implementing observability and reliability for AI pipelines. 

CI/CD, Automation & Developer Productivity 

• Build and maintain CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, or AWS CodePipeline.
• Automate deployments, environment provisioning, and release workflows.
• Build self-service developer platforms, preview environments, and reusable deployment workflows to improve developer productivity.
• Implement automated patching, scaling, backups, cleanup workflows, and drift detection. 

Containers, Kubernetes & Platform Reliability

• Manage Docker-based environments, containerized applications, and optimize workloads using Kubernetes (EKS) or ECS/Fargate.
• Manage autoscaling, cluster health, node pools, ingress, service mesh, and workload isolation.
• Optimize infrastructure for performance, resilience, and cost-efficiency.
• Implement progressive deployment strategies including blue/green, canary, and rolling deployments. 

Observability, Incident Response & SRE Practices

• Implement observability stacks using CloudWatch, Prometheus, Grafana, ELK, Datadog, OpenTelemetry, or New Relic.
• Build actionable dashboards and intelligent alerting systems while defining and tracking SLIs, SLOs, and SLAs.
• Lead incident response, root cause analysis, and blameless postmortems to reduce operational toil and improve MTTR.

FinOps, Cost Governance & Security

• Continuously monitor and optimize cloud costs (compute utilization, storage lifecycle, GPU usage, and data transfer) using AWS Cost Explorer, Budgets, Trusted Advisor, CloudHealth, or Kubecost.
• Implement AWS security best practices for IAM, VPCs, security groups, NACLs, encryption, and manage secrets using KMS, SSM Parameter Store, or Vault.
• Build secure CI/CD pipelines with automated security checks, least-privilege access, audit logging, and ensure compliance readiness for ISO 27001, SOC2, and GDPR.

Collaboration, Leadership & Platform Culture

• Work closely with engineering, AI/ML, QA, product, and operations teams to drive a DevOps, SRE, GitOps, and automation-first culture.
• Mentor junior DevOps and Platform Engineers while creating and maintaining detailed runbooks, architecture diagrams, and platform documentation.

Skills & Qualifications

Must-Have:

• 7+ years of experience in DevOps, SRE, Platform Engineering, or Cloud Infrastructure Engineering.
• Strong expertise in AWS cloud architecture, services, and deep understanding of Kubernetes (EKS), containers, and cloud-native systems.
• Strong Infrastructure-as-Code expertise using Terraform, CloudFormation, or CDK. Strong Linux administration, networking, DNS, routing, and load balancing knowledge. Strong scripting/programming experience in Python, Bash, or Go (preferred). Experience with CI/CD automation, GitOps workflows, and observability platforms supporting scalable production systems.

Preferred / Nice-to-Have:

• Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
• Familiarity with Kafka, Redis, SQS, and event-driven systems.
• Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
• AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 

Preferred / Nice-to-Have:

• Experience with AI/ML infrastructure, MLOps, model serving, vector databases, GPU orchestration, and inference optimization.
• Familiarity with Kafka, Redis, SQS, and event-driven systems.
• Exposure to platform engineering, internal developer platforms, and tools like ArgoCD, Flux, Helm, and OpenTelemetry.
• AWS Certifications: Solutions Architect, DevOps Engineer, or SysOps Administrator. Knowledge of distributed systems and large-scale platform operations. 

Here are answers to some questions you may have

Where is your office?

Chennai (Velachery)

Work Model

Work from Office – because great stories are built in person!

Do you have an online presence?

https://amura.ai (we are @AmuraHealth on all social media)

Requirements:

• Bachelor's degree in engineering with a specialization in computer science or a related field.
• 3+ years of experience as a software engineer in a product development setting.
• Love of technology and experience with one or more programming languages, such as Python
• Experience in full-stack development, including designing APIs and integration patterns, implementing security, and implementing frameworks for unit and end-to-end testing.
• Experience with microservices architecture.
• Experience in one or more frameworks like FastAPI, Spring, GRPC, Flask, etc.
• Extensive experience in a test-driven development environment.
• Understanding of CI/CD practices, including code check-in policies, automated unit tests, automated code deployments, etc.
• Ability to grasp new technologies and use them effectively to create industrial-strength software.
• Good communication skills. You can communicate well in the English language with product managers, your team members, and external stakeholders to understand their needs and convey yours in a clear, precise manner, verbally or in writing.
• Strong collaboration skills. You have demonstrated the ability to work with both senior and junior technical professionals and get work done. You quickly earn the trust of the people you work with. People enjoy and have fun working with you.
• Deadline-oriented. You understand that deadlines are meant to be met.
• Challenges will surface, and obstacles and roadblocks will cause delays, but you plan for them in advance and still ship your features on time to meet your commitments.
• Bias for action. Your default setting is to take action and not wait for things to happen. You love to learn about new technologies and advancements in the software industry.

Benefits at 314e Corporation:

• Medical Benefits
• Office Game space
• Referral Program
• Holiday parties

About the Role

We are hiring Staff / Principal Engineers to take full, hands-on ownership of Blitzy's most critical production-grade systems and to deliver high-leverage features that materially improve customer outcomes and engineering velocity. This is the most senior individual contributor role at the company today.

This is not a Senior-plus role, an architecture-only role, or a promotion-track role. We are looking for someone who has already operated at Principal / Staff+ scope in a highly technical environment and expects to spend their time writing, reviewing, and shipping production code.

This role is 100% hands-on. Leverage comes from system ownership, execution quality, and durable technical decisions — not people management or process.

Responsibilities

• Own mission-critical production systems end-to-end, ensuring correctness, scalability, performance, reliability, and operational excellence.
• Design, build, and ship high-impact backend systems and features that improve product reliability, performance, and customer value.
• Architect scalable services and cloud infrastructure using technologies such as Python, REST, gRPC, Kubernetes, and Terraform.
• Identify and resolve complex technical bottlenecks that limit engineering quality, system performance, or organizational velocity.
• Build and operate LLM-powered systems and validation loops that evaluate correctness, consistency, durability, and production performance.
• Design and evolve data architectures incorporating relational, NoSQL, graph, and vector databases to support complex enterprise applications and semantic retrieval.
• Modernize and improve complex enterprise systems while balancing reliability, maintainability, scalability, and delivery speed.
• Set and uphold engineering quality standards through hands-on technical leadership, sound technical judgment, and ownership of long-term technical decisions.

Qualifications

• Direct experience with Python as a primary programming language, backend frameworks, and microservices architectures.
• Expertise in REST and gRPC, with proficiency in Node.js and JavaScript.
• Proficiency in GCP, along with experience using at least one additional cloud platform such as AWS or Azure.
• Advanced knowledge of Kubernetes and Terraform in production environments.
• Experience operating highly available production systems, including monitoring, scalability, reliability, performance optimization, and operational tooling.
• Strong knowledge of SQL and NoSQL databases, including PostgreSQL, MySQL, MongoDB, Cassandra, or DynamoDB.
• Familiarity with graph databases such as Neo4j and vector databases or embedding infrastructure for semantic search and retrieval.
• Hands-on experience building and operating LLM-powered systems in production, including evaluation, validation, regression testing, tracing, and failure analysis.
• Working knowledge of LangSmith or comparable LLM observability and evaluation tools; familiarity with OpenAI, Anthropic, or similar model providers is a plus.
• Ability to contribute across the full stack, with a strong understanding of frontend architecture and the ability to debug, design, and ship across frontend, backend, infrastructure, and AI systems.
• Understanding of large-scale enterprise software systems, including architecture, integration, deployment, modernization, and long-term maintainability.
• Proven track record of operating at Staff+, Principal Engineer, or equivalent level, independently driving complex technical initiatives and delivering high-impact outcomes with minimal supervision.

Blitzy is a Cambridge, MA based AI software development platform on a mission to revolutionize the software development life cycle by autonomously building custom software to unlock the next industrial revolution. We're transforming how enterprises build software, turning enterprise requirements into enterprise grade code with an agentic software development platform that can autonomously execute 80% of the quantum of software development work. We're backed by multiple tier 1 investors, and have proven success as founders of previous start-ups.

Our Culture

Who we are:

Led by two pioneering co-founders we are one of the fastest growing companies in the U.S., creating our own category of enterprise autonomous software development. We automate thousands of hours of software development for our customers, which includes strong representation within the Fortune 500.

How we work:

• We move Blitzy Fast: Time is both our company’s and our clients’ most precious asset. We move quickly and decisively to innovate internally and deliver exceptional software externally.
• Championship Mindset: We operate like a professional sports team. We win as a team by holding ourselves and each other to high standards, collaborating in-person, and remaining focused on the mission.
• Passion for Invention: We’re pushing the frontier of what’s possible, requiring constant innovation and iteration.
• We Work for the Customer: We focus on delivering outsized value to the customers we work with and expanding those relationships into deep, meaningful partnerships.
• We believe in being ‘everyday athletes’: taking care of ourselves so we can bring our best minds to work. We promote great sleep, movement, and restorative activities for 

Blitzy is an equal opportunity employer committed to building a diverse and inclusive team. We believe different perspectives make us stronger.

Required Experience: 10–15 years (with at least 3–5 years in leadership roles)

● 10–15 years of overall experience in backend engineering, with strong exposure to

Python and/or Golang.

● 3–5 years of experience managing engineering teams.

● Proven experience delivering large-scale, distributed systems in production

environments.

● Strong understanding of microservices, cloud-native architecture, and DevOps

practices.

● Hands-on background in backend engineering (able to guide teams technically, even

if not coding daily).

● Familiarity with CI/CD pipelines, observability, and performance optimization.

● Experience in financial services or high-transaction domains is a plus.

● Experience leading teams that have utilized AI-driven development practices (e.g.,

agentic coding, LLM integration) to improve productivity and innovation is a

significant advantage.

Skills

● Excellent leadership and people management abilities.

● Strong communication and stakeholder management skills.

● Ability to balance technical depth with business priorities.

● Problem-solving mindset with a focus on delivery and impact.

● Passion for building engineering culture and improving developer experience.

Strong Python Developer profile with robust AWS exposure

2

Mandatory (Experience 1): Must have 7+ years of hands-on software development experience with at least the recent 4+ years in Python and strong hands on knowledge of AWS

3

Mandatory (Tech skill 1): Must have strong working knowledge of Python.

4

Mandatory (Tech skill 2): Must have good understanding of AWS services including EC2, S3, Lambda, IAM, CloudWatch, and ECS or ECR

5

Mandatory (Tech skill 3): Must be able to write and understand REST APIs

6

Mandatory (Tech skill 4): Experience designing and architecting scalable backend applications/services on AWS, including making decisions around application architecture, APIs, databases, and AWS services

7

Mandatory (Tech skill 5): Must be comfortable with version control tools such as Git, GitHub, Bitbucket, or GitLab

8

Mandatory (Tech skill 6): Must have good understanding of databases such as PostgreSQL, MySQL, or DynamoDB

9

Mandatory (Tech skill 7): Must have familiarity with Linux commands and shell scripting

10

Mandatory (Skill 1): Must have good debugging and problem-solving skills, with the ability to read existing code and make changes independently with light guidance

11

Mandatory (Skill 2): Must have strong communication skills

12

Preferred (Tech skill 2): Experience with AWS CodeCommit, and exposure to AWS CodeBuild, CodeDeploy, CodePipeline, GitHub Actions, Jenkins, or similar CI/CD tools

13

Preferred (Tech skill 3): Basic understanding of CI/CD pipelines

14

Preferred (Tech skill 4): Experience with Docker or container-based applications

15

Preferred (Tech skill 5): Basic knowledge of infrastructure-as-code tools such as Terraform or AWS CloudFormation