Member of Technical Staff: Developer (Bangalore, India)

Job Title : Python Django Developer

Experience : 3+ Years

Location : Gurgaon Sector - 48

Working Days : 6 Days WFO (Monday to Saturday)

Job Summary :

We are looking for a skilled Python Django Developer with strong foundational knowledge in backend development, data structures, and operating system concepts.

The ideal candidate should have experience in Django and PostgreSQL, along with excellent logical thinking and multithreading knowledge.

Main Technical Skills : Python, Django (or Flask), PostgreSQL/MySQL, SQL & NoSQL ORM, Microservice Architecture, Third-party API integrations (e.g., payment gateways, SMS/email APIs), REST API development, JSON/XML, strong knowledge of data structures, multithreading, and OS concepts.

Key Responsibilities :

• Write efficient, reusable, testable, and scalable code using the Django framework
• Develop backend components, server-side logic, and statistical models
• Design and implement high-availability, low-latency applications with robust data protection and security
• Contribute to the development of highly responsive web applications
• Collaborate with cross-functional teams on system design and integration

Mandatory Skills :

• Strong programming skills in Python and Django (or similar frameworks like Flask).
• Proficiency with PostgreSQL / MySQL and experience in writing complex queries.
• Strong understanding of SQL and NoSQL ORM.
• Solid grasp of data structures, multithreading, and operating system concepts.
• Experience with RESTful API development and implementation of API security.
• Knowledge of JSON/XML and their use in data exchange.

Good-to-Have Skills :

• Experience with Redis, MQTT, and message queues like RabbitMQ or Kafka.
• Understanding of microservice architecture and third-party API integrations (e.g., payment gateways, SMS/email APIs).
• Familiarity with MongoDB and other NoSQL databases.
• Exposure to data science libraries such as Pandas, NumPy, Scikit-learn.
• Knowledge in building and integrating statistical learning models.

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.

Responsibilities: 

• Help impacts software quality and customer experience (CX) of product features. 
• Able to convert an LLD into code. Codes may need some refinement. 
• Solutions are tested (continuously testable, when possible) and may need 
• refinement. 
• Able to write reusable and well-structured code. 
• Understands software architecture (layers, software component, etc), has 
• knowledge about patterns 
• Understand and can use Algorithms, Data structures in solving problems. 

Basic Qualification: 

• Bachelor's degree in computer science or related technical discipline 0-1 years of experience 
• Impactful internship, if fresher out of college- preferred with reputed techno-product orgs 
• Excellent Functional skills- understands software architecture (layers, software 
• components) and has knowledge about design patterns. 
• Programming experience with at least one modern language such as Java, Node.js including object-oriented design. 
• Computer science fundamentals in object-oriented design, data structures, algorithm design, problem solving, and complexity analysis. 

Responsibilities

- Software Engineering

- Design and develop highly scalable, available, reliable, secure and fault tolerant systems with minimal

guidance for a market leader in the logistics industry

- Partner with team members on functional and nonfunctional requirements and spread design

philosophy, goals and improve the code quality across the team

- Research new technologies and tools that enable building the next generation of our services

- Provide technology leadership to the team and foster engineering excellence

- Product Delivery

- Partner with product managers to define and execute on the feature roadmap

- Translate business requirements into scalable and extensible design

- Coordinate with various cross functional teams on planning and execution

- Maintaining automated build / test / deployment environments

Qualifications

- Software Engineering

- Should have at least 2 years of hands on experience in designing, developing, testing and deploying

applications on Java, Ruby, Kotlin, Python, Node or Go for large scale applications

- Deep knowledge of one of the programming language they have experience in

- Proficient in OOP and Design Patterns, experience with functional programming would be a plus

- Data modelling experience in Relational Databases

- Ability to design and implement low latency RESTful services

- Product Delivery

- Ability to scope, review and refine user stories for technical completeness and to alleviate dependency

risks.

- Well versed in working with agile methodologies which includes phases such as design, development,

code review, testing and release management

- Ability to have worked in a CI/CD environment, with hands on experience with Git or any similar source

code management tools

- Product Maintenance

- Experience troubleshooting server performance issues such as memory tuning, GC tuning, resource leaks

etc

- Continuously refactor applications to ensure high quality design.

• 2.5+ year of experience in Development in JAVA technology.
• Strong Java Basics
• SpringBoot or Spring MVC
• Hands on experience on Relationl Databases (SQL query or Hibernate) + Mongo (JSON parsing)
• Proficient in REST API development
• Messaging Queue (RabitMQ or Kafka)
• Microservices
• Any Caching Mechanism
• Good at problem solving

Good to Have Skills:

• 2+ years of experience in using Java/J2EE tech stacks
• Good understanding of data structures and algorithms.
• Excellent analytical and problem solving skills.
• Ability to work in a fast paced internet start-up environment.
• Experience in technical mentorship/coaching is highly desirable.
• Understanding of AI/ML algorithms is a plus.