Forward Deployed / Implementation Engineer 3 (Backend)

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.

Role Overview

We are seeking a Junior Developer with 1-3 year’s experience with strong foundations in Python, databases, and AI technologies. The ideal candidate will support the development of AI-powered solutions, focusing on LLM integration, prompt engineering, and database-driven workflows. This is a hands-on role with opportunities to learn and grow into advanced AI engineering responsibilities.

Key Responsibilities

• Develop, test, and maintain Python-based applications and APIs.
• Design and optimize prompts for Large Language Models (LLMs) to improve accuracy and performance.
• Work with JSON-based data structures for request/response handling.
• Integrate and manage PostgreSQL (pgSQL) databases, including writing queries and handling data pipelines.
• Collaborate with the product and AI teams to implement new features.
• Debug, troubleshoot, and optimize performance of applications and workflows.
• Stay updated on advancements in LLMs, AI frameworks, and generative AI tools.

Required Skills & Qualifications

• Strong knowledge of Python (scripting, APIs, data handling).
• Basic understanding of Large Language Models (LLMs) and prompt engineering techniques.
• Experience with JSON data parsing and transformations.
• Familiarity with PostgreSQL or other relational databases.
• Ability to write clean, maintainable, and well-documented code.
• Strong problem-solving skills and eagerness to learn.
• Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent practical experience).

Nice-to-Have (Preferred)

• Exposure to AI/ML frameworks (e.g., LangChain, Hugging Face, OpenAI APIs).
• Experience working in startups or fast-paced environments.
• Familiarity with version control (Git/GitHub) and cloud platforms (AWS, GCP, or Azure).

What We Offer

• Opportunity to work on cutting-edge AI applications in permitting & compliance.
• Collaborative, growth-focused, and innovation-driven work culture.
• Mentorship and learning opportunities in AI/LLM development.
• Competitive compensation with performance-based growth.

Strong Senior Backend Engineer profiles

Mandatory (Experience 1) – Must have 5+ years of hands-on Backend Engineering experience building scalable, production-grade systems

Mandatory (Experience 2) – Must have strong backend development experience using one or more frameworks (FastAPI / Django (Python), Spring (Java), Express (Node.js).

Mandatory (Experience 3) – Must have deep understanding of relevant libraries, tools, and best practices within the chosen backend framework

Mandatory (Experience 4) – Must have strong experience with databases, including SQL and NoSQL, along with efficient data modeling and performance optimization

Mandatory (Experience 5) – Must have experience designing, building, and maintaining APIs, services, and backend systems, including system design and clean code practices

Mandatory (Domain) – Experience with financial systems, billing platforms, or fintech applications is highly preferred (fintech background is a strong plus)

Mandatory (Company) – Must have worked in product companies / startups, preferably Series A to Series D

Mandatory (Education) – Candidates from top engineering institutes (IITs, BITS, or equivalent Tier-1 colleges) are preferred

We're hiring a Python Developer in Jaipur.

Not looking for someone who can recite design patterns. Looking for someone who can open a Django codebase, figure out what's broken,

 and fix it by end of day. 3-4 years. Django / Flask / FastAPI. REST APIs. PostgreSQL. If you've maintained production code (not just built tutorial projects) — this is your role.

Full-time | Jaipur | Industry-standard pay | Small team = real ownership

About Us

We began in 2015 with an entrepreneurial vision to bring a digital change in the manufacturing landscape of India. With a team of 1500(1k cluster guys) we are working towards the digital transformation of business in the manufacturing industry across domains like Footwear, Apparel, Textile, Accessories etc. We are backed by investors such as Info Edge (Naukri.com ), Matrix Partners, Sequoia, Water Bridge Ventures and select Industry leaders.

Today, we have enabled 4000+ Manufacturers to digitize their distribution channel.

Roles & Responsibilities

Writing and testing code, debugging programs and integrating applications with third-party web services. To be successful in this role, you should have experience using server-side logic and work well in a team.

Ultimately, you'll build highly responsive web applications that align with our business needs. Write effective, scalable code Develop back-end components to improve responsiveness and overall performance Integrate user-facing elements into applications.

Test and debug programs

Improve functionality of existing systems Implement security and data protection solutions Assess and prioritize feature requests

Coordinate with internal teams to understand user requirements and provide technical solutions Expertise in at least one popular Python framework (like Django, Flask, etc)

Team spirit

Good problem-solving skills

Requirements

1 to 5 years of experience as a Python Developer

Hands on experience of Flask, Django or Gin or Revel or Sanic

Knowledge of design/architectural patterns will be considered as a plus

Experience working in an agile development environment with a strong focus on rapid software development

Experience in AWS or similar cloud technologies

Excellent troubleshooting and debugging skills

Proven ability to complete assigned task according to the outlined scope and timeline

Experience with messaging frameworks such as SQS/Kafka/RabbitMq

Experience with Elastic Search

Willingness to learn new and different technologies

At Egnyte we develop content governance and collaboration products that are deployed across several large companies such as Yamaha and Red bull. The Egnyte platform supports daily, business critical operations for a million-plus user base interacting with a multi-petabyte content set.

We store, analyze, organize, and secure billions of files and petabytes of data with millions of users. We observe more than 1M API requests per minute on average. To make that possible and to provide the best possible experience, we rely on great engineers. For us, people who own their work from start to finish are integral. Our Engineers are part of the process from design to code, to test, to deployment, and back again for further iterations.  

We’re looking for Senior Software Engineers and he should be able to take a complex problem and work with product managers, devops and other team members to execute end to end.

• Design and develop scalable cloud components that seamlessly integrates with on-premises systems.
• Challenge and redefine existing architecture or make 10x improvements in performance and scalability.
• Ability to foresee post-deployment design challenges, performance and scale bottlenecks.
• Hire and mentor junior engineers
• Doing code reviews, unit and performance testing of the code.
• Monitor and manage 3000+ nodes using modern DevOps tools and APM solutions.

• Demonstrated success designing and developing complex cloud based solutions
• Solid CS fundamentals with one or more areas of deep knowledge
• Experience with the following technologies: Java, SQL, Linux, Python, Nginx, Haproxy, BigQuery, HBase, New Relic, memcache, Elasticsearch, docker.
• Data driven decision process
• Relies on automation testing instead of manual QA
• Experience in working with Google cloud, AWS or Azure is preferred

Candidates should have worked with Startups (IT Product Firms)

Should be from B2C Firms/Product/SaaS Firms

Key Skills: Python, Golang, Java, Distributed Systems, Cloud, Microservices Architecture, MVC, Design Patterns, Data Structure, Algorithms

Your Experience Across The Years in the Roles You’ve Played

• 6+ years of technology experience (at least 2 years in direct engineering management)
• Managing a 5-15 member engineering team in an agile product org
• Track record of collaborative working with multiple stakeholders
• Planning and analysis with effective communication skills

You’ll Be Improving & Responsible For

• Our products engineering team that works on initiatives fuelling the growth of our recent health retail insurance products
• Collaboration across cross-functional stakeholders to ensure delivery timelines are met
• Implementing product engineering best practices, and evangelizing them within the org
• Engineering management with a strong sense of ownership
• Problem solving with a clear and analytical approach and organized work habits
• Technological innovation in agile product engineering scenarios
• Product and business management principles and metrics