LoadShare Networks - Software Development Engineer III - Platform Engineering

LoadShare Networks; Bengaluru; On-site; INR 2,800,000 - 5,000,000; Full time

Job summary

LoadShare Networks is building a dedicated Platform Engineering function in Bengaluru to enhance developer experience, security, and AI infrastructure. You will own shared infrastructure, CI/CD pipelines, and self-service platforms enabling product teams to ship faster and more independently.

The role establishes AI SDLC practices and infrastructure to support AI-powered features with confidence, combining product thinking with infrastructure execution at scale.

Qualifications

• 4–8 years of professional software engineering experience with strong programming skills (Java, Python, or Node.js).
• Hands-on experience with cloud platforms (AWS/GCP/Azure) including networking, IAM, compute, and storage services.
• Proven experience designing and managing CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI, ArgoCD, or equivalent).
• Solid understanding of containerisation and orchestration (Docker, Kubernetes, ECS/EKS).
• Experience with infrastructure-as-code tools (Terraform, CloudFormation, or Pulumi).
• Working knowledge of secrets management (HashiCorp Vault or AWS Secrets Manager), security scanning, and compliance controls.
• Familiarity with code quality tooling such as SonarQube, linting frameworks, and static analysis.
• Exposure to AI workflows understanding of how LLM-based applications are built, evaluated, and deployed (prompt engineering, model APIs, RAG patterns, vector databases).
• Strong communication skills to work across product teams and influence without authority.
• Experience building internal developer platforms, self-service portals, or developer tooling.
• Hands-on experience with feature flag systems.
• Familiarity with service meshes, API gateways, and microservices patterns.
• Experience with observability stacks (Grafana, Prometheus, ELK, Datadog).
• Familiarity with AI agent frameworks and orchestration patterns for agentic workflows.
• Exposure to compliance frameworks such as SOC 2, ISO 27001, or PCI-DSS.
• Prior experience in a logistics, supply-chain, or high-throughput transactional environment.

Responsibilities

• Own the design and delivery of shared infrastructure and CI/CD pipelines across product engineering teams.
• Build self-service platforms and developer tooling to reduce friction and improve velocity.
• Define and enforce security, compliance, and AI SDLC practices across infrastructure and pipelines.
• Architect and manage cloud infrastructure (AWS/GCP), Docker/Kubernetes, and cost-optimisation initiatives.
• Lead AI platform harness and SDLC processes for AI-enabled features with governance and observability.

Skills

Java

Python

Node.js

AWS

GCP

Azure

Jenkins

GitHub Actions

GitLab CI

ArgoCD

Docker

Kubernetes

Terraform

CloudFormation

Pulumi

HashiCorp Vault

AWS Secrets Manager

SonarQube

Grafana

Prometheus

ELK

AI agent frameworks

Feature flags

Education

Bachelor's degree in Computer Science or related

Tools

Jenkins

GitHub Actions

GitLab CI

ArgoCD

Terraform

CloudFormation

Pulumi

Kubernetes

Docker

Grafana

Prometheus

ELK

HashiCorp Vault

Job description

About The Role

We are investing in a dedicated Platform Engineering function to improve developer experience, enforce security and compliance best practices, build the right AI infrastructure for the organisation, and drive technical innovation that yields measurable cost savings.

About The Role

We are investing in a dedicated Platform Engineering function to improve developer experience, enforce security and compliance best practices, build the right AI infrastructure for the organisation, and drive technical innovation that yields measurable cost savings.

As a Senior Platform Engineer, you will own the design and delivery of shared infrastructure, CI/CD pipelines, AI platform harnesses, developer tooling, and self-service platforms that enable our product engineering teams to ship faster, safer, and more independently.

You will also be responsible for establishing the AI software development lifecycle (SDLC) practices and infrastructure that allow teams across the org to build, evaluate, and deploy AI-powered features with confidence. This is a high-impact, high-autonomy role for someone who thinks like a product engineer but operates at the infrastructure layer.

What You Will Do

Developer Experience & Self-Service Platforms :

• Design and build self-service portals that allow product teams to create, configure, and test integrations independently without waiting on platform support.
• Own and evolve shared configuration servers, feature flag services, and common service libraries consumed across the organisation.
• Treat internal platforms as products to gather developer feedback, track adoption, and iterate continuously to reduce friction.

CI/CD, Code Quality & Delivery Pipelines

• Build and maintain standardised CI/CD pipelines for all product teams, covering automated builds, tests, security scans, and deployments.
• Standardise PR review workflows, deployment processes, and release management practices across the engineering org.
• Define and enforce code quality gates through SonarQube rules, linting policies, and automated checks that run Compliance & Governance :
• Implement and manage security controls including secrets management (Vault), secure file uploads, access policies, and vulnerability scanning.
• Ensure adherence to standard compliance frameworks (SOC 2, ISO 27001, or equivalent) at the infrastructure and tooling layer.
• Collaborate with InfoSec to embed security-by-default into every developer workflow and deployment pipeline.

Cloud Infrastructure & DevOps

• Work closely with the DevOps team to manage and optimize cloud infrastructure (AWS/GCP), container orchestration (Kubernetes/ECS), and Drive tech innovation projects focused on cost optimisation - right-sizing, spot instances, reserved capacity, and architectural changes that reduce cloud spend.
• Architect monitoring, observability, and alerting systems using tools like Grafana, Prometheus. Common Services & Platform Ownership
• Own the lifecycle of shared/common services consumed across multiple product verticals auth services, notification services, config servers, and more.
• Maintain service health, SLAs, and documentation for all platform-owned services.
• Lead the effort to clear existing technical debt and backlogs in the platform layer.

AI Infrastructure & AI SDLC

• Design and build the org-wide AI/ML platform harness including model serving infrastructure, prompt management, vector stores, evaluation pipelines, and LLM gateway/proxy layers.
• Establish AI SDLC best practices covering prompt versioning, model evaluation, A/B testing of AI features, cost tracking per model/call, and guardrails for responsible AI usage.
• Build shared tooling and abstractions that allow product teams to integrate LLMs, embeddings, and AI agents into their workflows without each team reinventing the stack.
• Set up observability for AI workloads latency tracking, token usage monitoring, hallucination detection, and cost dashboards across model providers.
• Stay current with the rapidly evolving AI tooling ecosystem and evaluate new frameworks, models, and infrastructure patterns for org-wide adoption.

Must-Have

What We Are Looking For :

• 4 - 8 years of professional software engineering experience with strong programming skills (Java, Python, or Node.js).
• Hands-on experience with cloud platforms (AWS preferred, GCP/Azure acceptable) including networking, IAM, compute, and storage services.
• Proven experience designing and managing CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI, ArgoCD, or equivalent).
• Solid understanding of containerisation and orchestration (Docker, Kubernetes, ECS/EKS).
• Experience with infrastructure-as-code tools (Terraform, CloudFormation, or Pulumi).
• Working knowledge of secrets management (HashiCorp Vault or AWS Secrets Manager), security scanning, and compliance controls.
• Familiarity with code quality tooling such as SonarQube, linting frameworks, and static analysis.
• Exposure to AI workflows understanding of how LLM-based applications are built, evaluated, and deployed (prompt engineering, model APIs, RAG patterns, vector databases).
• Strong communication skills you will work across product teams and need to influence without :
• Experience building internal developer platforms, self-service portals, or developer tooling.
• Hands-on experience with feature flag systems.
• Familiarity with service meshes, API gateways, and microservices patterns.
• Experience with observability stacks (Grafana, Prometheus, ELK, Datadog).
• Familiarity with AI agent frameworks and orchestration patterns for agentic workflows.
• Exposure to compliance frameworks such as SOC 2, ISO 27001, or PCI-DSS.
• Prior experience in a logistics, supply-chain, or high-throughput transactional environment.

Why This Role

• High ownership directly influence developer productivity and engineering velocity across the entire company.
• Breadth + depth a rare mix of programming, cloud infrastructure, DevOps, and product thinking in a single role.
• Innovation mandate dedicated time and space to explore new technologies and drive cost-saving innovations.
• AI-first trajectory build the AI infrastructure layer from scratch and define how the entire org adopts and ships AI-powered features.
• Growing team be part of a platform engineering team that is scaling up and shaping how engineering works across the org.

Team Structure

• You will be a senior individual contributor on the platform engineering team, working alongside DevOps engineers and collaborating closely with product engineering leads. You will report directly to the Director of Engineering
• Startup candidates are preferred (ref:hirist.tech)