Backend developer

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.

Role Overview:

We are seeking a backend-focused Software Engineer with deep expertise in REST APIs,

real-time integrations, and cloud-based application services. The ideal candidate will build

scalable backend systems, integrate real-time data flows, and contribute to system design

and documentation. This is a hands-on role working with global teams in a fast-paced, Agile

environment.

Key Responsibilities:

• Design, develop, and maintain REST APIs and backend services using Python, FastAPI,

and SQLAlchemy.

• Build and support real-time integrations using AWS Lambda, API Gateway, and

EventBridge.

• Develop and maintain Operational Data Stores (ODS) for real-time data access.

• Write performant SQL queries and work with dimensional data models in PostgreSQL.

• Contribute to cloud-based application logic and data orchestration.

• Containerize services using Docker and deploy via CI/CD pipelines.

• Implement automated testing using pytest, pydantic, and related tools.

• Collaborate with cross-functional Agile teams using tools like Jira.

• Document technical workflows, APIs, and system integrations with clarity and

consistency.

• Should have experience in team management

Required Skills & Experience:

• 8+ years of backend or integrations engineering experience.

• Expert-level knowledge of REST API development and real-time system design.

• Strong experience with: Python (FastAPI preferred), SQLAlchemy.

• PostgreSQL and advanced SQL.

• AWS Lambda, API Gateway, EventBridge.

• Operational Data Stores (ODS) and distributed system integration.

• Experience with Docker, Git, CI/CD tools, and automated testing frameworks.

• Experience working in Agile environments and collaborating with cross-functional

teams.

• Comfortable producing and maintaining clear technical documentation.

• Working knowledge of React is acceptable but not a focus.

• Hands-on experience working with Databricks or similar data platforms.

Education & Certifications:

• Bachelor’s degree in Computer Science, Engineering, or a related field (required).

• Master’s degree is a plus.

• Certifications in AWS (e.g., Developer Associate, Solutions Architect) or Python

frameworks are highly preferred.

WHO YOU ARE

To be successful in this role, you’ll need to have the following skills:

·         Love for coding: A fanatic about writing beautiful and scalable code.

·         A sense of analytics: Strong analytical and troubleshooting skills. Should be resourceful, innovative and inventive.

·         Dynamic: Should be comfortable in dealing with lots of moving pieces. Have exquisite attention to detail, and are comfortable learning new technologies and systems. 

·         Team player: Knack for influencing without being authoritative. Pitch in wherever the team needs help, from writing blog posts to supporting customers.

·         Accountability: High sense of ownership for your code and relentlessness to deliver projects with high business impact. 

KEY QUALIFICATIONS

·         BE/BTech in Computer Science or related field. 

·         5+ years of professional production and development experience with leading-edge server and database technologies (e.g., Python, Java, Node.js, Scala, Spring Boot, MySQL, and NoSQL databases).

KEY SKILLS

·         Strong computer system analysis and design skills in current methodologies and patterns Experience with professional production cloud (AWS preferred).

·         Experience with RESTful Services and APIs.

The Sr. Analytics Engineer would provide technical expertise in needs identification, data modeling, data movement, and transformation mapping (source to target), automation and testing strategies, translating business needs into technical solutions with adherence to established data guidelines and approaches from a business unit or project perspective.

Understands and leverages best-fit technologies (e.g., traditional star schema structures, cloud, Hadoop, NoSQL, etc.) and approaches to address business and environmental challenges.

Provides data understanding and coordinates data-related activities with other data management groups such as master data management, data governance, and metadata management.

Actively participates with other consultants in problem-solving and approach development.

Responsibilities :

Provide a consultative approach with business users, asking questions to understand the business need and deriving the data flow, conceptual, logical, and physical data models based on those needs.

Perform data analysis to validate data models and to confirm the ability to meet business needs.

Assist with and support setting the data architecture direction, ensuring data architecture deliverables are developed, ensuring compliance to standards and guidelines, implementing the data architecture, and supporting technical developers at a project or business unit level.

Coordinate and consult with the Data Architect, project manager, client business staff, client technical staff and project developers in data architecture best practices and anything else that is data related at the project or business unit levels.

Work closely with Business Analysts and Solution Architects to design the data model satisfying the business needs and adhering to Enterprise Architecture.

Coordinate with Data Architects, Program Managers and participate in recurring meetings.

Help and mentor team members to understand the data model and subject areas.

Ensure that the team adheres to best practices and guidelines.

Requirements :

- Strong working knowledge of at least 3 years of Spark, Java/Scala/Pyspark, Kafka, Git, Unix / Linux, and ETL pipeline designing.

- Experience with Spark optimization/tuning/resource allocations

- Excellent understanding of IN memory distributed computing frameworks like Spark and its parameter tuning, writing optimized workflow sequences.

- Experience of relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., Redshift, Bigquery, Cassandra, etc).

- Familiarity with Docker, Kubernetes, Azure Data Lake/Blob storage, AWS S3, Google Cloud storage, etc.

- Have a deep understanding of the various stacks and components of the Big Data ecosystem.

- Hands-on experience with Python is a huge plus

Backend Developer (Python)

Company and Founders
Egregore Labs (http://www.egregorelabs.com/">www.egregorelabs.com) is a financial software company founded in 2017 by Prashant Vijay (ISB, Tulane) & Hari Balaji (IIM Ahmedabad, IIT Madras) both of whom have spent over a decade each in Financial Services, with a majority of their experience at Goldman Sachs across New York, Hong Kong & Singapore in roles across Trading, Quant & Technology. More about the founders is available here and here

We operate at the intersection of Unstructured Data and Finance. We run multiple products, including Romulus (http://www.romulus.co/">www.romulus.co) and Robana (http://www.robana.ai/">www.robana.ai) - all our products work on the same underlying principles and set of technologies.

Ideal Background

• At least 2 years experience in back-end development in a fast-paced environment, working in Python
• Deep understanding of technologies used in web-deployed SaaS products, including Rest APIs
• Exposure to AWS, Azure or other cloud providers
• Sound understanding of computer science principles
• Exposure to any of the following
• Financial services
• Natural Language Processing
• Robotic Process Automation
• Intelligent Document Processing
• Document Management and Repositories

Opportunity
We will share our workload as a team and we expect you to work on a broad range of tasks. Here’s are some of the things you might have to do on any given day:

• Developing APIs and endpoints for deployments of our product
• Infrastructure Development such as building databases, creating and maintaining automated jobs
• Build out the back-end to deploy and scale our product
• Build POCs for client deployments
• Integrate our products with 3rd party products/tools/services
• Document your code, write test cases, etc.

Skills

• Hands-on experience with Python (2+ years)
• Sound understanding of Postgres and NoSQL databases such as MongoDB
• Deep familiarity with UNIX, major cloud platforms (AWS, Azure), DevOps
• Understanding of databases, and related tools, paradigms
• A computer science education would be great, but other engineering disciplines are ok as well

Desirables
We are looking for a person who has :

• Resourcefulness- - we're looking for versatile developers who are good at figuring out what they need to use, learn, build, re-purpose to get the job done quickly and efficiently.
• Ownership- - We like to be directive and not prescriptive in our management. We- d love for you to take ownership of what you work on, and tell us what to do, rather than the other way round.
• Work Ethic- - We- ve grown up on Wall Street. We work hard, and have aggressive goals. We want our team-mates to be focused, goal-oriented and consistent high achievers.
• Execution Focus- - Our business is about getting things done, and getting things done right. We want outcome focused colleagues who can multi-task, and execute quickly and elegantly.

Work From Home

Package: 7-12 LPA

Required Skills/Qualifications: 

∙         B.Tech/MCA in Comput

Required Skills/Qualifications: 

Any Backend Technology is acceptable

∙         B.Tech/MCA in Computer Science or equivalent with 1-3 years’ experience with server-side web application development.

∙         Extensive development experience using LAMP or MEAN stack, RESTful web services or Node.js, HTML and CSS.

∙         Good understanding of Data structures and Relational Databases like MySQL or NoSQL Databases like MongoDB.

∙         Experience working with services in AWS such as EC2, RDS, and ELBs and have knowledge of VPCs.

∙         Experience with server side and client side MVC frameworks, Kafka Ansilble,Jenkins.

∙         Exposure to Continuous Integration (CI) and Continuous Deployment (CD), automated testing and agile development methods.

∙         Understanding of Version Management Tools like GitHub.

er Science or equivalent with 1-3 years’ experience with server-side web application development.

∙         Extensive development experience using LAMP or MEAN stack, RESTful web services or Node.js, HTML and CSS.

∙         Good understanding of Data structures and Relational Databases like MySQL or NoSQL Databases like MongoDB.

∙         Experience working with services in AWS such as EC2, RDS, and ELBs and have knowledge of VPCs.

∙         Experience with server side and client side MVC frameworks, Kafka Ansilble,Jenkins.

∙         Exposure to Continuous Integration (CI) and Continuous Deployment (CD), automated testing and agile development methods.

∙         Understanding of Version Management Tools like GitHub.