SDE-3 (Python)

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.

AI Engineer — Vertexcover Labs

Who We Are

Vertexcover Labs is an employee-focused, engineer-run software studio. We partner with fast-growing, funded startups around the world—Rephrase.ai, Dhiwise, Dunzo, Dubdub, Xapo, Arintra etc.—to crack their toughest engineering problems. Everyone is an individual contributor; no management layers. Engineers choose the projects they work on, see each project's P&L, and share directly in the profits.

Whether it's building multi-agent systems for production, scaling ML pipelines across GPU clusters, or shipping RAG-powered products that end-users rely on—we solve hard AI problems for real companies.

A Few Problems We Are Currently Working On

• AI Agents Test-authoring agents that convert natural language into e2e tests.
• Ad-performance agents that learn what works for your brand and generate winning creatives automatically.
• Scale + MLOps Optimise ML pipelines and fix autoscaling by applying queuing theory while juggling CPU / GPU memory contention.
• RAG & Knowledge Systems Design and deploy retrieval-augmented generation pipelines—chunking strategies, embedding models, reranking, and evaluation loops.
• AI Video & Image Processing Build rendering pipelines, diffusion-model integrations, and real-time video processing at scale. You'll own at least one project like these—design, build, iterate.

Signals You're Probably the Right Fit

• Strong in at least one other language (Python, Go, Rust, TypeScript, Java …); happy to learn more.
• First principle understanding of how LLMs, embeddings, vector databases and AI Agents work
• Evidence of shipping real AI-powered software—OSS, side projects, or production features.
• Comfortable navigating the fast-moving AI landscape—papers, new model releases, evolving APIs.
• Clear written & spoken communication; async collaboration is our default.
• Self-directed—you ask for context, not permission.

How We Operate

• Project choice. Engineers vote on which engagements we take.
• Stack agnostic. We pick tools that fit the job, not the résumé.
• Pragmatic craftsmanship. Durable design, no gold-plating.
• Transparent economics. Know what your work is worth, share in the profits.
• Remote-native. Async by default; sync when it helps.

Hiring Process (Lean & Human)

1. 2–3 technical deep-dives with future teammates.
2. 30-minute culture chat.
3. Offer. No LeetCode marathons, no trick puzzles.

We read every application and reply to all candidates.

Strong Full stack/Backend engineer profile

Mandatory (Experience): Must have 2+ years of hands-on experience as a full stack developer (backend-heavy)

Mandatory (Backend Skills): Must have 1.5+ strong experience in Python, building REST APIs, and microservices-based architectures

Mandatory (Frontend Skills): Must have hands-on experience with modern frontend frameworks (React or Vue) and JavaScript, HTML, and CSS

Mandatory (Database Skills): Must have solid experience working with relational and NoSQL databases such as MySQL, MongoDB, and Redis

Mandatory (Cloud & Infra): Must have hands-on experience with AWS services including EC2, ELB, AutoScaling, S3, RDS, CloudFront, and SNS

Mandatory (DevOps & Infra): Must have working experience with Linux environments, Apache, CI/CD pipelines, and application monitoring

Mandatory (CS Fundamentals): Must have strong fundamentals in Data Structures, Algorithms, OS concepts, and system design

Mandatory (Company) : Product companies (B2B SaaS preferred)

We are looking Python intern/developer role. We are looking for candidates who are strong in core Python skills, able to work independently, and strong in developing logic.

• Need to develop the new script using Perl  & Python
• Need to analyse the existing script and do new changes
• Need to interact with QA team, Deployment team
• Need to interact with in-house and external customers
• Need to interact with internal team members for integrated development
• Need to have good communication skills within the team members

Skills required:

• Need to have experience in developing projects using PERL and Python
• Familiarity in Unix/Linux development environments and tools including
• scripting and  process management
• Need to have experience in database(Mysql) concepts
• Need to have a experience in Elastic Search
• Have a knowledge in Git,Svn commands
• Need to have experience in implementing OOPS concepts
• Need to have a experience in XML functionality (read,create.,etc)
• Have a knowledge in creating a csv,xlsx files, json format
• Need to have a experience in PDF Functionality & FTP,SFTP Modules
• Need experience in unit testing
• Develop best practices to ensure coding efficiency and quality
• Experience in test driven development and Agile methodologies

Preference of Educational background:

• B.E

Preference of Professional background:

• Experience in handling  modules
• Experience in  PERL,Python,Mysql,Linux,Elastic search,Xml,PDF,FTP functionality

• 3+ years of recent hands-on Java development
• Java, Python, JavaScript programming languages
• Fluency with RESTful APIs, AngularJS, HTML5 and CSS
• Great understanding of designing for performance, scalability, and reliability of data intensive application
• Understanding of database fundamentals and advanced SQL knowledge
• In-depth understanding of object oriented programming concepts and design patterns
• Ability to communicate clearly to technical and non-technical audiences, verbally and in writing
• Understanding of full software development life cycle, agile development and continuous integration
• Experience in Agile methodologies including Scrum and Kanban

What puts you over the top:

• Exposure to various technologies like Spring Boot, Microservices, Kubernetes and also some frontend technologies like React.js, Node.js or other UI frameworks.

●  Experience in AdTech or Programmatic

MUST HAVE GOOD EXPERIENCE IN SPRING BOOT, NODE JS, ANGULAR JS, REACT JS, JAVASCRIPT,JAVA, HTML/CSS.