
Our client is a global leader in providing Omni-channel strategy, marketing, creative and technology services that uniquely connects companies to talent. Their goal is to improve how employers source, hire, engage, and retain talent, while creating an interactive experience that keeps job seekers top-of-mind. They provide client's access to a suite of integrated cloud based solutions and services with capabilities to source, nurture, and engage, the right-fit candidates.
All about the role :
- Senior Associate in India in the product engineering team acts as a partner to the business and provides technical leadership in one or more of our product lines. This individual will play a key role in product design, integration architecture, implementation, quality and product releases.
This person will report into Tech Manager/Architect.
- We are looking for a Senior level Lead NodeJS developer with advanced knowledge of NodeJS + Angular to join our product development team to build and extend a world class SaaS based Programmatic Media/Marketing Automation services.
Skills and Experience :
- Must have extensive experience with building services with Node.JS and related technologies
- Must have experience with SQL and database schema design
- Must have previous experience in leading a team
- Experience with RESTful web services, CSS, HTML5 is desirable
- Hands-on experience AngularJS/Angular
- Should have experience with any of the unit testing frameworks (eg: mocha). Working knowledge with quality plugins like jslint, jshint, jsbeautify, Istanbul would be an advantage.
- Experience with designing and building APIs with REST/Microservices
- Good to have knowledge with AWS Lambda & supporting configuration knowledge.
- Knowledge with any of the serverless frameworks like Serverless, AWS SAM would be an advantage.
- Must have experience with SCM tools with code repository & related operations (branching, merging, pull requests etc)
- Good to have knowledge with API Gateway and CloudFront.
- Good to have - Experience with various Core Java technologies and frameworks
- Experience with performance optimization and security vulnerabilities resolution would be an advantage
- Should have good communication skills, ability to work in a team (spread across geographies), problem solving skills & eye for detail. Leadership & Management
- Imbibe and represent our culture, core values and ensure the behavior and feedback is cascaded through the organization
- Provide feedback to the leadership team by demonstrating understanding of business, markets, and industry trends and needs.
- Own the growth plans of self, peers and team members in the product engineering teams.
Education and Experience Requirements :
- Bachelor's degree in Engineering or relevant fields.
- 6-9 years of experience in a role of a senior developer in technology and product development teams with at least 3 years of experience in leading a team.
- Experience of working in a global distributed development model.
- Track record of delivering high performance products.
- Experience of developing products and solutions in a SAAS model and cloud based technologies
- Product / Development Company background
- B2C / B2B prod experience
- Domain - digital - E-commerce, marketing, social, mobile, java
- Hands on tech with ability to manage or lead other developers in the team

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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.
Position: Python Developer
Location: Andheri East, Mumbai
Work Mode: 5 Days WFO
Availability: Immediate joiners only (or notice period completed)
What We're Looking For:
✅ 2+ years of solid Python development experience
✅ Django framework expertise - must have!
✅ FastAPI framework knowledge - essential!
✅ Database skills in MongoDB OR PostgreSQL
✅ Ready to work from office 5 days a week
Role & Responsibilities
work with peers in Product, QA, and other Engineering departments;
coach and mentor team members;
cautiously drive adoption of new technologies and processes;
preserve our engineering values of quality, scalability, and maintainability;
“see around corners” — identify blind spots and prioritize work across teams;
work with international teams to ensure successful product development and delivery; and
own the overall architecture and systems engineering for your products.
Core AI Backend Engineer – LLM Fine-Tuning
You know that moment when you don’t just debug code — you train a model, fine-tune it, and suddenly it understands your domain better than you expected? That’s the kind of magic we’re looking for.
We’re building something that turns chaotic social video data into crystal-clear business intelligence. Not just another API — but AI-backed architecture fine-tuned to our world. Systems that marketing teams thank you for, because they feel the intelligence, not just the infrastructure.
Either you feel the craft when you read this, or you don’t. This isn’t just another backend role. This is where you bring together scalable systems and cutting-edge LLMs to build something the world hasn’t seen before.
Who We Are
We’re a small, global team that ships fast. Every line of code and every model choice affects millions of video analysis requests.
Our engineers don’t just build APIs — they architect solutions, they optimize at scale, and now, they fine-tune models to make AI work in the real world. Our CPTO still codes. Our senior engineers make complexity look effortless. Our backend team sets a standard that others ask how we move so fast.
What We Need
We need someone who’s lived both sides of this life:
- Backend excellence: building high-scale, high-performance systems.
- LLM fine-tuning: hands-on with open-source models, not just calling APIs.
Someone who can sit with a requirement at 2pm and by 6pm not only has endpoints working, but also has a fine-tuned model running behind them — customized to our use case.
Your Craft
- JavaScript/TypeScript & NodeJS as core backend tools.
- Next.js for full-stack where needed.
- Rust when performance is non-negotiable.
- Golang/Python as comfortable tools of choice.
- MySQL/Postgres/Redis — wielded with intention.
- AWS ecosystem — your playground, not your puzzle.
- LLM/AI integration you’ve actually shipped.
- Open-source LLM fine-tuning experience:
- Bringing in open-source models (LLaMA, Mistral, Falcon, etc.).
- Fine-tuning/adapting them for specific domains.
- Optimizing for inference cost, latency, and accuracy.
The Reality
The work is beautifully complex. The scale is real and growing. The problems are the kind that wake you up at 3am with solutions.
If you get your energy from building backend systems and adapting LLMs to make them smarter for real-world use, you’ll probably fall in love with what we do. If you’re only interested in APIs without touching models, this won’t be your thing — and that’s completely okay.
How to Apply
If you’re reading this thinking “finally, a team that actually cares about real AI engineering” — we’d love to see something you’ve built.
Not just a resume. Show us your craft:
- An LLM fine-tuning repo.
- A domain-adapted model you worked on.
- A system design where you combined backend and AI.
- Or even a short write-up or voice note explaining what you’ve fine-tuned.
We’re genuinely excited to see what you’ve done and have a meaningful conversation about whether this could be magic for both of us.
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- Basic understanding of front-end technologies, such as JavaScript, HTML5, and CSS3
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.NET C# developer provides custom web application development using the .NET Framework, C#, http://VB.NET">VB.NET, http://ASP.NET">ASP.NET, SQL Server and other advanced components of Microsoft technology and provide training to programmer analysts who support the web services manager' responsibilities.
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The tool development also involves working with SQL queries and web front end
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Managing source code with Git, including Gitlow WorkflowPosition: Backend Developer 1 / Backend Engineer:
Location: Bangalore
Experience: .5 to 4 years, preferably in an agile environment
Strong Knowledge Node.js and MongoDB
Good Knowledge on Flask, SQL and other databases
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