
- Experience in Python
- Experience in any Framework like Django, and Flask.
- Primary and Secondary skills - Python, OOPs and Data Structure
- Good understanding of Rest Api
- Familiarity with event-driven programming in Python
- Good analytical and troubleshooting skills

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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.
🚀 Hiring: Java Developer at Deqode
⭐ Experience: 2 Years
📍 Location: Indore
⭐ Work Mode:- 5 Days Work from Office
⏱️ Notice Period: Immediate Joiners
(Only immediate joiners & candidates serving notice period)
💫 Responsibilities:
✅ Develop and maintain Java applications
✅ Work with Spring/Spring Boot & REST APIs
✅ Debug, optimize, and improve application performance
✅ Design and implement Microservices & REST APIs
Mandatory skills
Hands on Python Programming.5+ years of Data Engineering experience: Skills sets: Python, SQL (Snowflake), S3.
Good to have
AWS familiarity would help
Responsibilities:
● Design, develop, and maintain scalable backend services and APIs using Java and Spring
Boot.
● Create and optimize SQL database schemas and queries in PostgreSQL to ensure efficient
data storage and retrieval.
● Implement RESTful APIs to facilitate seamless communication between frontend and backend
components.
● Configure and manage Nginx web servers to efficiently handle incoming requests and improve
application performance.
● Deploy and manage applications on AWS or GCP, ensuring scalability, reliability, and
security.
● Configure and optimize message broker systems using Kafka for real-time data processing
and communication.
● Containerize applications using Docker for easy deployment, scaling, and management.
● Create detailed Low-Level Designs (LLDs) and High-Level Designs (HLDs) to guide the
development and architecture of backend systems.
● Automating CI/CD pipelines and streamlining the software development lifecycle.
● Integrate AI/ML models into backend workflows using Python, PyTorch/TensorFlow, or
third-party AI APIs.
● Leverage AI tools (e.g., OpenAI APIs, Hugging Face, AWS AI services) to build intelligent
features.
● Collaborate closely with frontend developers, product managers, data scientists, and other
stakeholders to deliver high-quality AI-powered solutions.
● Monitor and troubleshoot production systems to ensure optimal performance, reliability, and
uptime.
What We’re Looking For:
● Bachelor’s degree in Computer Science, Engineering, or related field.
● 3-5 years of experience in backend development.
● Proficiency in Java, Spring Boot, PostgreSQL, SQL, and GitActions.
● Strong understanding of RESTful API design principles and best practices.
● Experience with configuring and optimizing Nginx web servers.
● Experience with configuring and optimizing Kafka service.
● Hands-on experience with AWS or GCP.
● Familiarity with Docker containers and container orchestration.
● Ability to create comprehensive Low-Level Designs (LLDs) and High-Level Designs (HLDs)
for backend systems.
● Experience with Python for AI/ML model integration in backend services.
● Familiarity with AI platforms and APIs such as OpenAI, Hugging Face, AWS AI/ML, or GCP
Vertex AI.
● Excellent problem-solving skills and attention to detail.
● Strong communication and collaboration skills, with the ability to work effectively in a team
environment.
Preferred Qualifications:
● Knowledge of microservices architecture and related technologies.
● Experience with cloud-native development and serverless computing.
● Understanding of software development best practices, including Agile methodologies
Company is building a math-learning platform with a meticulously designed curriculum that helps students become 4x quicker and better at math by nurturing their cognitive abilities and building their core math acumen.
Responsibilities:
• Design, develop, test, deploy and maintain software
• Delivering high quality and well-structured code
• Manage individual project priorities and deadlines
• Participate in enhancing tools and processes
• Participate in production observance and technical incident management
• Ability to quickly learn and adapt to keep up in a fast-paced environment
Must haves:
• Strong data structure concepts
• Great problem-solving skills
• Working knowledge of at least one or more of Java / JavaScript / C / C++ / Golang / Python
• Exposure to RDBMS and/or NoSQL databases
• Working knowledge of GitHub, CI/CD, Devops
Good to have:
• Any cloud exposure like AWS, GCP or Azure
• Hands-on experience with Docker containers, Kubernetes etc
Key Responsibility Areas:
- Develop tools and applications by producing clean, efficient code.
- Determine operational feasibility by evaluating analysis, problem definition, requirements, solution development and proposed solutions
- Perform validation and verification testing and debud code.
- Work collaboratively with others to achieve goals
- Experience working in an agile environment
Required Skills:
- Experience in implementing Object-Oriented Python, Django.
- Good understanding on Django
- Experienced in interfacing with *third party API’s using REST
- Worked with varieties of Relational Databases (RDBMS) like SQLite, MySQL, PostgreSQL.
- Experience in Version Control with Git and Bitbucket.
- Experience with JIRA the development progress and tracking deadlines of the project
Good knowledge and experience of working with backend systems;
designing server-side architecture, including production maintenance experience are must-haves.
At least 1-2 years of experience in any programming languages like Java, Ruby, PHP, Python and Node.js(Node.js preferred).
Understanding of micro-services oriented architecture.
Experience with Databases design (SQL, NoSQL) and analytics
Experience in driving and delivering complex features/software modules from technical design to launch.
Expertise with unit testing & Test Driven Development (TDD)
Primary Responsibilities
HouseItt is a student-run start up recognized by the start-up India initiative by the
Government of India. It provides student residences across and around Delhi University
colleges. It provides easy to book, better service, and affordable rental homes to students
within the campus and thrives on building a robust support system for handling student
accommodations. It bridges the gap between the demand (students looking for PGs/Flats)
and supply (owners) of rentals.
JOB PROFILE: BACKEND DEVELOPER (FULL-TIME JOB)
REQUIREMENTS:
• Good knowledge of MongoDB or framework like Django (Python).
• Proficient in MySQL, PostgreSQL.
• Proficient understanding of Git & Github.
• Knowledge of user authentication and authorization between multiple systems, servers,
and environments.
• A solid understanding of how Web Apps work including security and session
management.
• Adequate knowledge of relational database systems and OOPconcepts.
• Experience with testing tools like Sentry.
• Ability to learn and research about things you don't know.
ROLES AND RESPONSIBILITIES:
• Understanding and interpreting the task assigned by Team Lead.
• Getting the assigned work done in the given deadline.
• Giving suggestions to improve our web application and solve business problem.
TENURE: Full-time job
LOCATION: Work from Home
SALARY: Rs. 20000/- to Rs. 25000 (IN HAND)
BENEFITS:
• Certificate of Experience
• Letter of Recommendation








