Developers, System Admins and DevOPS/SRE and release engineers

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.

● Proven experience in training, evaluating and deploying machine learning models

● Solid understanding of data science and machine learning concepts

● Experience with some machine learning / data engineering machine learning tech in Python (such as numpy, pytorch, pandas/polars, airflow, etc)

● Experience developing data products using large language model, prompt engineering, model evaluation.

● Experience with web services and programming (such as Python, docker, databases etc.)  

● Understanding of some of the following: FastAPI, PostgreSQL, Celery, Docker, AWS, Modal, git, continuous integration. 

Kognitos is a cutting-edge automation platform that combines the power of Generative AI and Natural

Language Processing (NLP) to provide a conversational and intuitive experience for business users. As a

fully serverless, SaaS automation platform, Kognitos enables users to build, manage, and execute

automations in natural language, with the ability to process and understand domain-specific language.

Kognitos provides a detailed auditable view of its runs, allowing users to gain insights into why an action

happened or what might have gone wrong in case of an exceptional situation. Additionally, Kognitos's

conversational exception handling, powered by Generative AI, allows for quick and easy resolution of

unexpected system errors or business exceptions.

Responsibilities:

- Develop and maintain the backend infrastructure for our applications using Python and AWS Serverless

technologies.

- Collaborate with cross-functional teams to design and implement scalable and robust systems, including

microservices and cloud-based architectures.

- Ensure the reliability, scalability, and performance of the backend systems through monitoring and

optimization.

- Create and maintain database schema and queries to support the application features.

- Write unit and integration tests for the backend code and ensure code quality through code reviews.

- Continuously improve the software development process by incorporating best practices and modern

software development methodologies, such as Agile, DevOps, and CI/CD.

- Investigate and troubleshoot production issues and provide timely solutions to minimize downtime and

ensure smooth operations.

- Participate in architectural discussions and contribute to the development of technical solutions and best

practices.

- Stay up to date with the latest technologies and trends in software development and recommend

improvements to the technology stack to increase efficiency and scalability.

- Work in a fast-paced, collaborative environment with a focus on delivering high-quality software that

meets customer needs.

Required Experience/Skills:

- B.S. or higher degree in Computer Science/Engineering or similar field or equivalent work experience

- 4-20 years of industry experience (or equivalent)

- Proficient in Python programming language

- Experience with modern software development practices and methodologies, including Agile, DevOps,

and Continuous Integration/Continuous Delivery (CI/CD).

- Experience with large-scale distributed systems, microservices, and cloud-based architectures.

- Strong understanding of software design patterns, algorithms, data structures, and database technologies.

- A natural problem solver, with the ability to identify problems and lead the development of a solution.

• Proven working experience in web programming.
• Top-notch Programming skills and in-depth knowledge of modern HTML5/CSS/jQuery.
• Familiarity with at least one of the following programming languages: PHP, ASP.NET, JavaScript.
• A solid understanding of how web applications work including security, session management, and best development practices.
• Adequate knowledge of relational database systems, Object Oriented Programming and web application development.
• Hands-on experience with network diagnostics, network analytics tools.
• Basic knowledge of the Search Engine Optimization process.
• Aggressive problem diagnosis and creative problem-solving skills.
• Strong organizational skills to juggle multiple tasks within the constraints of timelines and budgets with business acumen.
• Ability to work and thrive in a fast-paced environment, learn rapidly and master diverse web technologies and techniques.
• BCA/MCA/B.Tech/BSc in computer science or a related field

Job Summary
We are looking for a PHP Developer responsible for managing back-end services and the interchange of data between the server and the users. Your primary focus will be the development of all server-side logic, definition and maintenance of the central database, and ensuring high performance and responsiveness to requests from the front-end. You will also be responsible for integrating the front-end elements built by your co-workers into the application. Therefore, a basic understanding of front-end technologies is necessary as well.

• Minimum experience should be 5 years.
• Strong knowledge of PHP frameworks (such as OpenCart, Zend)
• Advance understanding of front-end technologies, such as JavaScript & JS based frameworks like jquery.

• Understanding of MVC design patterns.

• Good hands on in integrating payment API's and CRM software development.

• Preference for experience on rest API's.

• Proficient understanding of code versioning tools, such as Git.

Role and Responsibilities

• Build a low latency serving layer that powers DataWeave's Dashboards, Reports, and Analytics functionality
• Build robust RESTful APIs that serve data and insights to DataWeave and other products
• Design user interaction workflows on our products and integrating them with data APIs
• Help stabilize and scale our existing systems. Help design the next generation systems.
• Scale our back end data and analytics pipeline to handle increasingly large amounts of data.
• Work closely with the Head of Products and UX designers to understand the product vision and design philosophy
• Lead/be a part of all major tech decisions. Bring in best practices. Mentor younger team members and interns.
• Constantly think scale, think automation. Measure everything. Optimize proactively.
• Be a tech thought leader. Add passion and vibrance to the team. Push the envelope.

Skills and Requirements

• 8- 15 years of experience building and scaling APIs and web applications.
• Experience building and managing large scale data/analytics systems.
• Have a strong grasp of CS fundamentals and excellent problem solving abilities. Have a good understanding of software design principles and architectural best practices.
• Be passionate about writing code and have experience coding in multiple languages, including at least one scripting language, preferably Python.
• Be able to argue convincingly why feature X of language Y rocks/sucks, or why a certain design decision is right/wrong, and so on.
• Be a self-starter—someone who thrives in fast paced environments with minimal ‘management’.
• Have experience working with multiple storage and indexing technologies such as MySQL, Redis, MongoDB, Cassandra, Elastic.
• Good knowledge (including internals) of messaging systems such as Kafka and RabbitMQ.
• Use the command line like a pro. Be proficient in Git and other essential software development tools.
• Working knowledge of large-scale computational models such as MapReduce and Spark is a bonus.
• Exposure to one or more centralized logging, monitoring, and instrumentation tools, such as Kibana, Graylog, StatsD, Datadog etc.
• Working knowledge of building websites and apps. Good understanding of integration complexities and dependencies.
• Working knowledge linux server administration as well as the AWS ecosystem is desirable.
• It's a huge bonus if you have some personal projects (including open source contributions) that you work on during your spare time. Show off some of your projects you have hosted on GitHub.