9+ Distributed Systems Jobs in Mumbai | Distributed Systems Job openings in Mumbai

Location: Mumbai, Maharashtra, India

Sector: Technology, Information & Media

Company Size: 500 - 1,000 Employees

Employment: Full-Time, Permanent

Experience: 10 - 14 Years (Engineering Leadership)

Level: Engineering Manager / Group EM

ABOUT THIS MANDATE :

Recruiting Bond has been exclusively retained by one of India's most prominent and well-established digital platform organisations operating at the intersection of Technology, Information, and Media to identify and place an exceptional Engineering Manager who can lead engineering teams through an enterprise-wide AI adoption and digital transformation agenda.

This is a high-impact, hands-on leadership role at the nexus of people, product, and technology. The organisation is executing one of the most ambitious AI transformation programmes in its sector and this Engineering Manager will be a core driver of that change. You will lead multiple squads, own engineering delivery end-to-end, embed AI tooling and practices into the team's DNA, and shape the engineering culture of tomorrow.

We are seeking leaders who code when it matters, who build systems and teams with equal conviction, and who view AI not as a trend but as a fundamental shift in how great software is built.

THE OPPORTUNITY AT A GLANCE :

AI-First Engineering Culture :

• Own AI adoption across your squads - from LLM tooling integration to automation-first delivery workflows. Make AI a default, not an afterthought.

Hands-On Engineering Leadership :

• Stay close to the code. Lead architecture reviews, unblock engineers, and set the technical bar - not just the management agenda.

People & Org Builder :

• Grow engineers into leaders. Build squads of 615 across functions. Drive hiring, career frameworks, and a culture of psychological safety.

KEY RESPONSIBILITIES :

1. Hands-On Technical Engagement :

• Remain deeply embedded in the technical work participate in design reviews, architecture decisions, and critical code reviews
• Set and uphold the engineering quality bar : performance benchmarks, security standards, test coverage, and release quality
• Provide technical direction on backend platform strategy, API design, service decomposition, and data architecture
• Identify and resolve systemic technical debt and architectural risks across team-owned services
• Unblock engineers by diving into complex problems debugging, pair programming, and system analysis when it matters
• Own key technical decisions in collaboration with Tech Leads and Principal Engineers; balance pragmatism with long-term sustainability

2. AI Adoption, Integration & Transformation (2026 Mandate) :

• Define and execute the team's AI adoption roadmap - from developer tooling to product-facing AI features
• Champion the integration of GenAI tools (GitHub Copilot, Cursor, Claude, ChatGPT) across the full engineering workflow coding, testing, documentation, incident response
• Embed LLM-powered capabilities into the product : recommendation engines, intelligent search, conversational interfaces, content generation, and predictive systems
• Lead evaluation and adoption of AI-assisted SDLC practices : automated code review, AI-generated test suites, intelligent observability, and anomaly detection
• Partner with Data Science and ML Platform teams to productionise ML models with robust MLOps pipelines
• Build team literacy in prompt engineering, RAG (Retrieval-Augmented Generation), and AI agent frameworks
• Create an experimentation culture : run structured AI pilots, measure productivity impact, and scale what works
• Stay ahead of the AI tooling landscape and advise senior leadership on strategic AI investments and engineering implications

3. People Leadership & Team Development :

• Lead, manage, and grow squads of 6 - 15 engineers across seniority levels (L2 through L6 / Junior through Staff)
• Conduct structured 1 : 1s, career growth conversations, and development planning with every direct report
• Design and execute personalised AI upskilling programmes ensure every engineer develops practical AI fluency by end of 2026
• Build and maintain a high-performance team culture : clarity of ownership, accountability, fast feedback loops, and psychological safety
• Drive performance management fairly and rigorously recognise top performers, manage underperformance constructively
• Lead technical hiring end-to-end : define job requirements, conduct bar-raising interviews, and make data-driven hire decisions
• Contribute to engineering career frameworks and level definitions in partnership with the VP / Director of Engineering

4. Engineering Delivery & Execution Excellence :

• Own end-to-end delivery for multiple product squads from planning and scoping through production release and post-launch stability
• Implement and refine agile delivery frameworks (Scrum, Kanban, Shape Up) calibrated to squad needs and product cadence
• Drive predictable delivery : maintain healthy sprint velocity, manage WIP limits, and ensure dependency resolution across teams.
• Establish and own engineering KPIs : DORA metrics (deployment frequency, lead time, MTTR, change failure rate), uptime SLOs, and velocity trends
• Lead incident management : build blameless post-mortem culture, own RCA processes, and drive systemic reliability improvements
• Balance technical debt repayment with feature velocity negotiate prioritisation transparently with Product leadership

5. Strategic Leadership & Cross-Functional Influence :

• Serve as the primary engineering partner for Product, Design, Data, and Business stakeholders translate ambiguity into executable engineering plans
• Participate in quarterly roadmap planning, capacity forecasting, and OKR definition for engineering teams
• Represent engineering in leadership forums articulate technical constraints, risks, and opportunities in business terms
• Contribute to org-wide engineering strategy : platform investments, build-vs-buy decisions, and shared infrastructure priorities
• Build relationships across geographies (Mumbai HQ + distributed teams) to maintain alignment and delivery cohesion
• Act as a culture carrier and ambassador for engineering excellence, innovation, and responsible AI use

AI TRANSFORMATION LEADERSHIP 2026 EXPECTATIONS :

In 2026, Engineering Managers at this organisation are expected to be active architects of AI transformation not passive observers. The following outlines the specific AI leadership expectations for this role :

AI Developer Productivity

• Drive measurable uplift in developer velocity through AI tooling adoption. Target : 30%+ reduction in code review cycle time and 40%+ increase in test coverage automation by Q3 2026.

LLM & GenAI Product Features

• Own delivery of GenAI-powered product capabilities : intelligent content, semantic search, personalisation, and conversational UX in production, at scale.

AI-Augmented Observability

• Implement AI-driven monitoring and anomaly detection pipelines. Reduce MTTR by leveraging predictive alerting, intelligent runbooks, and auto-remediation scripts.

Team AI Fluency :

• Build mandatory AI literacy across all engineering levels.
• Every engineer understands prompt engineering basics, AI ethics guardrails, and responsible AI deployment practices.

Responsible AI Governance :

• Partner with Security, Legal, and Data Privacy to ensure all AI deployments meet compliance standards, bias mitigation requirements, and explainability benchmarks.

TECHNOLOGY STACK & DOMAIN FAMILIARITY REQUIRED :

• Languages: Java/ Go/ Python/ Node.js /PHP /Rust (must be hands-on in at least 2)
• Cloud: AWS / GCP / Azure (multi-cloud exposure strongly preferred)
• AI & GenAI: OpenAI / Anthropic / Gemini APIs /LangChain /LlamaIndex / RAG / Vector DBs / GitHub
• Copilot: Cursor /Hugging Face
• Containers: Docker /Kubernetes /Helm /Service Mesh (Istio / Linkerd)
• Databases: PostgreSQL /MongoDB / Redis / Cassandra / Elasticsearch / Pinecone (Vector DB)
• Messaging: Apache Kafka /RabbitMQ /AWS SQS/SNS /Google Pub/Sub
• MLOps & DataOps: MLflow /Kubeflow / SageMaker / Vertex AI /Airflow /dbt
• Observability: Datadog /Prometheus /Grafana /OpenTelemetry / Jaeger /ELK Stack
• CI/CD & IaC: GitHub Actions ArgoCD / Jenkins / Terraform /Ansible /Backstage (IDP)

QUALIFICATIONS & CANDIDATE PROFILE :

Education :

• B.E. / B.Tech or M.E. / M.Tech from a Tier-I or Tier-II Institution - CS, IS, ECE, AI/ML streams strongly preferred
• Demonstrated engineering depth and leadership impact may complement institution pedigree

Experience :

• 10 to 14 years of progressive engineering experience, with at least 3 years in a formal Engineering Manager or equivalent people-leadership role
• Proven track record of managing and scaling engineering teams (615+ engineers) in a fast-growing SaaS or digital product environment
• Hands-on backend engineering background must be able to read, write, and critique production code
• Direct experience driving AI/ML feature delivery or AI tooling adoption within engineering organisations
• Exposure across start-up, mid-size, and large-scale product organisations, preferred adaptability is a core requirement
• Strong CS fundamentals: distributed systems, algorithms, system design, and software architecture
• Demonstrated career stability minimum of 2 years of average tenure per organisation.

The Ideal Engineering Manager in 2026 :

• Leads with context, not control, empowers engineers while maintaining accountability and quality
• Is fluent in both people language and technical language, switches registers naturally with engineers and executives alike
• Sees AI as a force multiplier for the team, not a threat. Actively experiments with and advocates for AI tooling
• Measures success by team outcomes, not personal output. Takes pride in what the team ships, not what they build alone
• Creates feedback loops obsessively between product and engineering, between seniors and juniors, between metrics and decisions
• Has strong opinions, loosely held, brings conviction to discussions but updates on evidence
• Invests in engineering excellence as seriously as delivery velocity knows that quality and speed are not opposites

WHY THIS ROLE STANDS APART :

AI Transformation at Scale :

• Lead one of the most significant AI adoption programmes in India's digital media sector.
• Our decisions will shape how hundreds of engineers work in 2026 and beyond.

Hands-On & Strategic Balance :

• A rare EM role that actively encourages technical depth.
• Stay close to the code while owning the people agenda - the best of both worlds.

Established Platform, Real Scale :

• 5001,000 engineers, proven product-market fit, and the org maturity to execute.
• This is not a greenfield startup gamble it is a serious company with serious ambition.

Clear Leadership Growth Path :

• A visible, direct path toward Director / VP of Engineering.
• Senior leadership is invested in growing its next generation of technology executives.

• Looking for candidate who is enthusiastic to work in a Startup environment and build things from Scratch individually
• Candidate has past experience in scalable consumer facing applications managing latency and traffic
• FullStack Individual Contributor with experience to code at speed and take full product ownership

Experience: minimum 8 YRS

Location: Vile parle (E), Mumbai

Skill Set: 8 years plus as a full stack Java/JavaScript Developer

Micro Services, Distributed Systems

Cloud Services: AWS:(EC2,S3,Lambda,Load Balancing,Serverless),Kubernates

Programming Backend: Node.js,Mongodb,Java Spring,PostGreSQL

Programming FrontEnd: ,Angular/React

Queuing: Kafka

Methodologies: Agile Scrum

Responsibilities:

End to end coding ; from software architecture to managing scaling,of high throughput(100000)RPS high volume transactions.

DIscuss business requirements and timelines with management and create a task plan for junior members.

Manage the day to day activities of all team members and report

their work progress

Mentoring the team on best coding practices and making sure modules are Live

on time.

Management of security vulnerabilities.

Be a full individual contributor which means can work in a team as well as alone.

Attitude:

Passion for tech innovation and solve problems

GoGetter Attitude

Extremely humble and polite

Experience in Product companies and Managing small teams is a plus

At Egnyte we develop content governance and collaboration products that are deployed across several large companies such as Yamaha and Red bull. The Egnyte platform supports daily, business critical operations for a million-plus user base interacting with a multi-petabyte content set.

We store, analyze, organize, and secure billions of files and petabytes of data with millions of users. We observe more than 1M API requests per minute on average. To make that possible and to provide the best possible experience, we rely on great engineers. For us, people who own their work from start to finish are integral. Our Engineers are part of the process from design to code, to test, to deployment, and back again for further iterations.  

We’re looking for Senior Software Engineers and he should be able to take a complex problem and work with product managers, devops and other team members to execute end to end.

• Design and develop scalable cloud components that seamlessly integrates with on-premises systems.
• Challenge and redefine existing architecture or make 10x improvements in performance and scalability.
• Ability to foresee post-deployment design challenges, performance and scale bottlenecks.
• Hire and mentor junior engineers
• Doing code reviews, unit and performance testing of the code.
• Monitor and manage 3000+ nodes using modern DevOps tools and APM solutions.

• Demonstrated success designing and developing complex cloud based solutions
• Solid CS fundamentals with one or more areas of deep knowledge
• Experience with the following technologies: Java, SQL, Linux, Python, Nginx, Haproxy, BigQuery, HBase, New Relic, memcache, Elasticsearch, docker.
• Data driven decision process
• Relies on automation testing instead of manual QA
• Experience in working with Google cloud, AWS or Azure is preferred

• End-to-end ownership of new feature development, from design, through implementation, testing, deployment, and maintenance in production
• Translating of high-level requirements and end-user use cases into design proposals, including integration with external services and constraints of underlying service infrastructure
• Maintaining constant focus on scalability, performance and robustness of a feature, on the top of base functional implementation
• Designing and implementing logging, monitoring and alerting functions as core parts of overall software solution
• Documenting your own work and design solutions
• Decomposing complex features into smaller, short-term deliverable tasks
• Managing priorities of multiple tasks, providing up-to-date estimates for a milestone delivery

• 5+ of industry experience in technical leadership roles
• Solid knowledge of Go-Lang, Python, C/C++, SQL, shell scripting and Linux operating environment.
• End-to-end experience in design and development of highly scalable enterprise and cloud data products.
• Ability to challenge and redefine existing architectural fundamentals in order to provide next level of performance and scalability; ability to foresee post-deployment challenges.
• Hands-on experience with design and troubleshooting of scalable web services, advanced file systems, geographic replication, distributed databases and modern operating systems.
• Experience with modern DevOps technologies such as Docker and container orchestration, service deployment, monitoring and scaling
• Ability to work with multi-cultural, globally distributed teams to a common unifying product vision and closely coordinate with cross-functional teams in different time-zones.
• Passion to deliver enterprise-grade products to customers and to continuously work with engineering team to refine the product in the field.

• Lead a small group of highly talented engineers to build platform components to power various micro services.
• Responsible for end-to-end architecture of Platform. Leads High- & Low-level design of critical components.
• Mentor other Senior & Lead engineers
• Lead a small group of highly talented engineers to build platform components to power various micro services.
• Responsible for end-to-end architecture of Platform. Leads High- & Low-level design of critical components.
• Mentor other Senior & Lead engineers