Software Engineer I/II

Required Skills & Qualifications

• 4+ years of professional experience in backend development with Python.
• Strong hands-on experience with FastAPI (or Flask/Django with migration experience).
• Familiarity with asynchronous programming in Python.
• Working knowledge of version control systems (Git).
• Good problem-solving and debugging skills.
• Strong communication and collaboration abilities.
• should have a solid background in backend development, RESTful API design, and scalable application development.

Shift: Night Shift 6:30 pm to 3:30 AM IST

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 Summary:

As a Shopify App Developer at [Your Company Name], you will be responsible for designing, developing, and maintaining custom applications for the Shopify platform. You will collaborate with cross-functional teams to create solutions that meet our clients' needs and improve their eCommerce operations. The ideal candidate will have a strong background in Shopify app development, excellent problem-solving skills, and a passion for delivering exceptional user experiences.

Key Responsibilities:

• App Development: Design, develop, and deploy custom Shopify apps using Shopify’s API, Polaris, and other relevant technologies.
• Customization: Customize and extend Shopify’s existing functionalities to meet specific client requirements.
• Integration: Integrate Shopify apps with third-party services, APIs, and data sources as needed.
• Maintenance & Support: Troubleshoot and resolve issues related to Shopify apps and provide ongoing support and maintenance.
• Collaboration: Work closely with project managers, designers, and other developers to ensure that app solutions align with project goals and client expectations.
• Testing & Quality Assurance: Conduct thorough testing of applications to ensure reliability, performance, and adherence to Shopify’s standards.
• Documentation: Create and maintain clear documentation for code, processes, and app functionality.
• Innovation: Stay updated with the latest Shopify developments, industry trends, and best practices to continuously improve app functionality and user experience.

Qualifications:

• Experience: Proven experience in developing Shopify apps, including a portfolio of past projects or apps.
• Technical Skills: Proficiency in Shopify’s APIs, Liquid templating language, JavaScript, HTML, CSS, and familiarity with Shopify Polaris design system.
• Programming Languages: Strong knowledge of backend programming languages such as Ruby, PHP, or Node.js.
• Database Management: Experience with database technologies such as MySQL, MongoDB, or PostgreSQL.
• Problem-Solving: Excellent problem-solving skills with the ability to troubleshoot and resolve complex technical issues.
• Communication: Strong verbal and written communication skills, with the ability to explain technical concepts to non-technical stakeholders.
• Team Player: Ability to work effectively both independently and as part of a team in a fast-paced environment.

At Upswing, we are a passionate and self-driven team of thinkers who aspire to build the rails to connect the legacy financial sector with financial innovators through a simple and powerful banking-as-a-service (BaaS) platform.

We’re building our platform putting the focus on pragmatism, reliability, and maintainability. We believe that keeping the engineering complexity under control is key to preserving the development productivity and long-term evolution of a platform.

To bring this vision to life, we are building the infrastructure using Microservices architecture using the latest set of technologies that are also fun to work with such as Java, Scala, Postgres, Akka, Kafka with a completely automated DevOps pipeline from the get-go using tools like Chef, Jenkins, Grafana, Graylog.

We are looking for motivated engineers who will be working in a highly creative and cutting edge technology environment to build a world-class financial services suite.

Why you should join us:

• You will redefine the financial services landscape for India in the coming years.
• Be part of a core Engineering team that will create innovative and scalable Fintech solutions.
• Work with passionate and experienced engineering, product & business workforce that believes in teamwork, and that helps fast-track your learning on solving complex technical challenges.
• We are funded by the leading fintech VC `QED Investors` and other established Founders and Executives of awesome Indian companies.

What you will do if you join us:

• Propose solutions to solve complex system architecture challenges and actively lead the end-to-end development of the system.
• Create robust, flexible, consistent, and easy-to-use APIs
• Continuously strive for performance improvements, code reusability, and readability

You should have:

• Tech or a higher degree in computer science or a related field.
• 1+ years of experience working on the back-end development for complex distributed systems who are willing to adopt any Programming language as per the requirement.
• Familiarity with any of the following – Java, C++, Scala, Kotlin, and frameworks like Spring, Play, Hibernate, Django, etc.
• Good understanding of Algorithms, Data Structure, OOP, Design patterns, Parallel programming, Multithreading concepts & Event-Driven Systems.
• Experience with Relational databases such as MySQL, PostgreSQL, Oracle, or any NoSQL database.

It’s a plus if you have:

• Familiarity with cloud platforms like AWS, Azure, or Google Cloud
• Worked on Micro-services architecture

• Experience 4 – 5 years
• Good in Backend Springboot
• write Rest API (Should be strong in this area)
• Good Analytical ability, Good coding practice, Knowledge of Spring Security (Desirable),
• UI Knowledge of Angular (Average knowledge should be enough)