Responsibilities
- Develop, deploy, and maintain scalable products
- Participate in code reviews, and design discussions to ensure code quality and distribute knowledge
- Pair with team members for functional and non-functional requirements to write well-crafted, well-tested, readable, and maintainable code.
- Help to define roadmap and architecture based on technology and business needs
- Understand business requirements and work closely with the business to provide solutions
Eligibility
- Strong expertise in Backend Python Development with skills to create APIs, integrate the functions into UI, and store and retrieve data from a variety of databases.
- Strong experience with Django/Flask.
- Strong experience in writing unit tests.
- B.Tech/B.E (Preferred CSE)

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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.
We are seeking an experienced Senior Backend Engineer to join our passionate team. If you have a strong background in backend development, a track record of delivering scalable and reliable solutions, and are eager to contribute to complex projects, we would love to hear from you.
Responsibilities:
- Design and develop robust, high-performance backend solutions using Python and related technologies.
- Lead the architecture and design discussions for major backend components and services.
- Collaborate closely with cross-functional teams to gather and analyze software requirements.
- Mentor and guide junior and mid-level engineers, fostering their technical growth.
- Review code and provide constructive feedback to ensure code quality and adherence to best practices.
- Identify and address performance bottlenecks, scalability challenges, and technical issues.
- Participate in sprint planning, task estimation, and agile development processes.
- Keep up-to-date with industry trends, tools, and best practices to continuously improve our backend systems.
- Drive the adoption of coding standards, design patterns, and engineering best practices.
- Collaborate with frontend engineers to ensure seamless integration between frontend and backend components.
Requirements:
- Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent experience).
- Minimum of 4 years of professional experience in backend development.
- Strong proficiency in Python and backend frameworks like Django and Flask.
- In-depth knowledge of database systems, both relational (MySQL) and NoSQL (MongoDB, etc. ).
- Proven track record of designing and developing scalable and maintainable backend services.
- Experience with RESTful API design and best practices.
- Solid understanding of software architecture, design principles, and software development lifecycle.
- Previous experience leading or mentoring engineers is a strong plus.
- Strong problem-solving skills and a proactive attitude towards challenges.
- Excellent communication skills, both verbal and written.
- Familiarity with cloud platforms (e. g., AWS, Azure, GCP) and containerization (Docker) is a plus.
Responsibilities
· Develop Python-based APIs using FastAPI and Flask frameworks.
· Develop Python-based Automation scripts and Libraries.
· Develop Front End Components using VueJS and ReactJS.
· Writing and modifying Docker files for the Back-End and Front-End Components.
· Integrate CI/CD pipelines for Automation and Code quality checks.
· Writing complex ORM mappings using SQLAlchemy.
Required Skills:
· Strong experience in Python development in a full stack environment is a requirement, including NodeJS, VueJS/Vuex, Flask, etc.
· Experience with SQLAchemy or similar ORM frameworks.
· Experience working with Geolocation APIs (e.g., Google Maps, Mapbox).
· Experience using Elasticsearch and Airflow is a plus.
· Strong knowledge of SQL, comfortable working with MySQL and/or PostgreSQL databases.
· Understand concepts of Data Modeling.
· Experience with REST.
· Experience with Git, GitFlow, and code review process.
· Good understanding of basic UI and UX principles.
· Project excellent problem-solving and communication skills.
Primary Skills: Database Systems (SQL), Python Flask/Fast API/Django frameworks specifically
Requirements:
- Highly proficient in fundamentals of Python web development frameworks like Flask, Django and Fast API
- Demonstrated experience in developing APIs using Python frameworks
- Should have deep knowledge in PostgreSQL, MS SQL Server and other SQL based Databases
- Knowledge and proficiency in NoSQL is a bonus
JOB DESCRIPTION
DYT - Do Your Thng, is an app, where all social media users can share brands they love with their followers and earn money while doing so! We believe everyone is an influencer. Our aim is to democratise social media and allow people to be rewarded for the content they post. How does DYT help you? It accelerates your career through collaboration opportunities with top brands and gives you access to a community full of experts in the influencer space.
RESPONSIBILITIES
- Expert in Python with knowledge of Python best practices (PEP8)
- Strong knowledge of python web frameworks such as Django, Flask • Strong knowledge of building RESTful APIs using Django Rest Framework • Good Understanding of Django ORM Libraries
- Able to integrate multiple data sources and databases into one system • Strong experience on Linux
- Solid database skills in a relational database (i.e. PostgresSQL,MYSql) • Able to create database schemas that represent and support business processes • Strong unit test and debugging skills
- Proficient understanding of code versioning tools (git)
- Experience deploying on AWS is desirable
- Experience with Docker,Test Drive Development will be a plus
- Excellent interpersonal, leadership, influence and communication skills • Experience in designing scalable micro-services is desirable
QUALIFICATIONS
- 1-3 years of experience as a backend developer
- At least one product build and published
- SKILLS Contribute in all phases of the development lifecycle
- Write well designed, testable, efficient code
- Work well under pressure and meet deadlines without sacrificing quality • Work with distributed development teams
Looking Data Enginner for our OWn organization-
Notice Period- 15-30 days
CTC- upto 15 lpa
Preferred Technical Expertise
- Expertise in Python programming.
- Proficient in Pandas/Numpy Libraries.
- Experience with Django framework and API Development.
- Proficient in writing complex queries using SQL
- Hands on experience with Apache Airflow.
- Experience with source code versioning tools such as GIT, Bitbucket etc.
Good to have Skills:
- Create and maintain Optimal Data Pipeline Architecture
- Experienced in handling large structured data.
- Demonstrated ability in solutions covering data ingestion, data cleansing, ETL, Data mart creation and exposing data for consumers.
- Experience with any cloud platform (GCP is a plus)
- Experience with JQuery, HTML, Javascript, CSS is a plus.
1. Ability to read the documentation and perform 3rd party API integrations
2. Experience with Postgres and Redis
3. Experience with AWS - EC2, RDS, DynamoDB, etc
4. Experience with Python
Dashboard
Skills
1. Experience with Django
a. Django Web
b. Django REST
c. Django Channels
d. Django Celery (Queues and Brokers)
2. Experience creating a dashboard with login, user profiles, roles and permissions, reports
3. Experience with Facebook and Twitter OAuth
4. Experience with handling database migrations
Chatbot
Skills
1. Basic understanding of NLP - intents and entities
2. Strong understanding of dialogue management and conversation flow
3. Integrations with Facebook and Twitter APIs.
4. Creating and managing Facebook and Twitter apps
5. Understanding of webhooks and REST APIs.











