.net Full stack 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.

Job Description

Build and maintain bots on Azure platform.  Integration with Active directory, WEB API based integration with external systems. Training and Integrate bots as per users’ requirements. Work in line with design guidelines, best practices and standards of bot deliverable. Creative approach to the conversation flow design, human aspects in the bot responses and sentiments

Qualifications

1. a) 5 years of experience in software development with clear understanding of the project life cycle
   b) Min 2-3 years of hands-on experience in Microsoft Azure Bot Framework, LUIS and other Cognitive services offered by Azure
   c) Hands on experience with Machine Learning based chat bots
   d) Experience with Azure bot services like Text Analytics etc.
   e)Strong database skills and hands-on experience on databases like SQL Server/Oracle
2. f) Strong experience on Azure Active directory and adaptive cards integration in Chat bot.
3. g) Strong experience designing and working with

with service-oriented architectures (SOA) and WebAPIs.

1. h) A strong experience on Microsoft Azure, ASPNET / MVC and programming languages such as C#/VBNET
2. i) Knowledge of Python and NodeJS is a plus
3. j) Ability to design and optimize SQL Server 2008 stored procedures.
4. k) Experience with JQuery, CSS3, HTML5 or similar technologies.

🔧 Key Skills

• Strong expertise in Python (3.x)
• Experience with Django / Flask / FastAPI
• Good understanding of Microservices & RESTful API development
• Proficiency in MySQL/PostgreSQL – queries, stored procedures, optimization
• Solid grip on Data Structures & Algorithms (DSA)
• Comfortable working with Linux & Windows environments
• Hands-on experience with Git, CI/CD (Jenkins/GitHub Actions)
• Familiarity with Docker / Kubernetes is a plus

• Manage different versions of complicate code and distribute them to different teams in the organization utilizing TFS.
• Develop an ASP.Net application to input and manage a production schedule, production statistical analysis and trend reporting.
• Create routines for importing data utilizing XML, CSV and comma delimitate files.
• Filter and cleanse OLTP data with complex store procedures and SSIS packages in the staging area.
• Develop a dimensional database and OLAP cube using SSAS for analysis, maintenance and good customer service.
• Involve in development and implementation of SSIS, SSRS and SSAS application solutions for various business units across the organization.
• Extract the data from XML and load it to dimensional model.
• Maintain SQL scripts, indexes, complex queries for data analysis and extraction.
• Create advanced reports like dashboard and scoreboard using SharePoint and power pivot for better presentation of data.
• Create cubes in SSAS reports which require complex calculations such as calculation of the premium for a particular policy.
• Create SharePoint sub sites, lists, libraries, folders and apply site permissions according to the given requirement.
• Work with business analysts, subject matter experts, and other team members to determine data extraction and transformation requirements.
• Develop T-SQL functions and store procedures to support complex business requirements.
• Create and configure an OLTP replication database for disaster recovery purpose.
• Designed/Implemented/Maintain OLAP servers and processes to replicate production data to the server.

* Minimum 2 year relevant experience in .Net or .Net core server-side programming as last

working relevant experience.

* Basic Engineering Knowledge – OOPS , Data Structure , memory management etc..

* Hands on experience in .Net, WCF (optional) and windows concept

* Hands on experience in SQL – basic are must to have

* Requirement analysis and design principle understanding is required

* Good in unit testing and debugging concepts

* Should be good in communication.

Mandatory skillset - SQL, REST API / GRPC

Job Location-Gurgaon (Hybrid)

Early joiners with a notice period of 15 days to 1 month will be preferred.

Intro

We are looking for an Software Engineer (SDE1) to join our team and drive the technology growth of our pay later platform. At Rely, we want passionate and talented individuals that want a challenge building the next generation payment products for Millennials across Asia. Together we will build the best products using amazing technology.

What will you do

• Design and implement business critical, high performance large scale services.
• Translate business requirements into scalable and extensible design.
• Coordinate with cross functional teams (Data, UX, QA etc.) on planning and execution.
• Continuously improve code quality, product execution and customer delight.
• Proactively manage stakeholder communication related to deliverables, risks, changes and dependencies.
• Building and managing automated build/test/deployment environments.
• Work with team members on functional and nonfunctional requirements and spread goals across the team.
  
  

What will you need

• 2+ years of hands-on experience with python and a backend framework (ideally django)
• 1+ years Hands-on experience working with Javascript and JS frameworks (Angular, React)
• Hands-on experience in designing, developing, testing and deploying applications large scale applications in any language or stack
• Experience working with high scale distributed systems.
• Practical knowledge of scalable software design.
• Good working knowledge of AWS
• Proficient with APIs, web protocols, OAuth, git.
• Ability to understand and implement Continuous Integration and Continuous Delivery.
• Well versed with Lean methodologies, TDD and Test Engineering and Automation.
• Ability to design and implement low latency RESTful services.
• Willingness to learn new languages and methodologies.

What would be a bonus

• Experience in production environments with large data sets
• Experience in scaling systems to millions of users.
• Work experience in a fast-growth startup
• Experience in DevOps tools but not limited to Docker, Kubernetes
• Experience in Gunicorn and Nginx