
Must have skills : Experience with Core Java, Microservices, Oracle Database and SpringBoot.
Roles & Responsibility :
- Build new decentralized microservices based on decoupled Kafka architecture
- Thorough understanding of fundamentals including OOP, Design Patterns and Data Structures
- Good knowledge of design principles
- Produce clean, efficient code based on specifications
- Recommend and implement improvements
- Has proven ability to work independently or with minimal supervision
- Drive design discussions while also working with architects if a need arises
Required Skills :
- Experience building software applications professionally using Java.
- Strong understanding of troubleshooting methodologies and root cause analysis
Soft skills required :
- Excellent interpersonal and written communication skills.
- Able to pre-empt, identify and resolve problems that are non-routine or lacking in definition
- Ability to define, implement and work to a schedule
- Good time management skills.
- Attention to detail. Able to work with little or no supervision
- Ability to work with team members across the globe
- Experience with Core Java, Angular and SpringBoot is a plus.
Educational Qualifications : B.E./ ME (CS/EE) / MCA or equivalent higher-level degree

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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.
Job Title : Java Backend Developer
Experience : 3 – 8 Years
Location : Pune (Onsite) (Pune candidates Only)
Notice Period : Immediate to 15 Days (or serving NP whose LWD is near)
About the Role :
We are seeking an experienced Java Backend Developer with strong hands-on skills in backend microservices development, API design, cloud platforms, observability, and CI/CD.
The ideal candidate will contribute to building scalable, secure, and reliable applications while working closely with cross-functional teams.
Mandatory Skills : Java 8 / Java 17, Spring Boot 3.x, REST APIs, Hibernate / JPA, MySQL, MongoDB, Prometheus / Grafana / Spring Actuators, AWS, Docker, Jenkins / GitHub Actions, GitHub, Windows 7 / Linux.
Key Responsibilities :
- Design, develop, and maintain backend microservices and REST APIs
- Implement data persistence using relational and NoSQL databases
- Ensure performance, scalability, and security of backend systems
- Integrate observability and monitoring tools for production environments
- Work within CI/CD pipelines and containerized deployments
- Collaborate with DevOps, QA, and product teams for feature delivery
- Troubleshoot, optimize, and improve existing modules and services
Mandatory Skills :
- Languages & Frameworks : Java 8, Java 17, Spring Boot 3.x, REST APIs, Hibernate, JPA
- Databases : MySQL, MongoDB
- Observability : Prometheus, Grafana, Spring Actuators
- Cloud Technologies : AWS
- Containerization Tools : Docker
- CI/CD Tools : Jenkins, GitHub Actions
- Version Control : GitHub
- Operating Systems : Windows 7, Linux
Nice to Have :
- Strong analytical and debugging abilities
- Experience working in Agile/Scrum environments
- Good communication and collaborative skills
Responsibilities :
● Designing and developing robust and scalable server-side applications using Python, Flask, Django, or other relevant frameworks and technologies.
● Collaborating with other developers, data scientists, and data engineers to design and implement RESTful APIs, web services, and microservices architectures.
● Writing clean, maintainable, and efficient code, and reviewing the code of other team members to ensure consistency and adherence to best practices.
● Participating in code reviews, testing, debugging, and troubleshooting to ensure the quality and reliability of applications.
● Optimizing applications for performance, scalability, and security, and monitoring the production environment to ensure uptime and availability. ● Staying up-to-date with emerging trends and technologies in web development, and evaluating and recommending new tools and frameworks as needed.
● Mentoring and coaching junior developers to ensure they grow and develop their skills and knowledge in line with the needs of the team and the organization.
● Communicating and collaborating effectively with other stakeholders, including product owners, project managers, and other development teams, to ensure projects are delivered on time and to specification.
You are a perfect match, if you have these qualification :
● Strong experience in Python and server-side development frameworks such as Flask or Django.
● Experience in building RESTful APIs, web services, and microservices architectures.
● Experience in using database technologies such as MySQL, PostgreSQL, or MongoDB.
● Familiarity with cloud-based platforms such as AWS, Azure, or Google Cloud Platform.
● Knowledge of software development best practices such as Agile methodologies, Test-Driven Development (TDD), and Continuous Integration/Continuous Deployment (CI/CD).
● Excellent problem-solving and debugging skills, and the ability to work independently as well as part of a team.
● Strong communication and collaboration skills, and the ability to work effectively with other stakeholders in a fast-paced environment
Responsibilities:
- Provide technical leadership of critical integrations by MuleSoft mostly with contact-center solution.
- Provide MuleSoft technical expertise and leadership when evaluating and designing integration solutions ensuring all components and subsystems impacted are properly addressed during builds and deployments.
- Collaborate cross-functionally with teammates to implement integration solution.
- Troubleshoot MuleSoft/API technical issues as needed
Qualifications
- Bachelor's Degree required. In lieu of a degree, a comparable combination of education and experience may be considered.
- 3+ years of experience in building scalable, highly available, distributed solutions and services
- 1+ years of experience in middleware technologies: Enterprise Service Bus (ESB), most preferably with MuleSoft CloudHub and Orchestration, Routing and Transformation
- 3+ years of experience working with Java
- Experience in RESTful API architectures, specifications and implementations
- Working knowledge of progressive development processes like scrum, XP, Kanban, TDD, BDD and continuous delivery
- Concept understanding on Google Cloud platforms is a major plus
Enterprise Minds, with core focus on engineering products, automation and intelligence, partners customers on the trajectory towards increasing outcomes, relevance and growth.
Harnessing the power of Data and the forces that define AI, Machine Learning and Data Science, we believe in institutionalizing go-to-market models and not just explore possibilities.
We believe in a customer-centric ethic without and people-centric paradigm within. With a strong sense of community, ownership, and collaboration our people work in a spirit of co-creation, co-innovation and co-development to engineer next-generation software products with the help of accelerators.
Through Communities we connect and attract talent that shares skills and expertise. Through Innovation Labs and global design studios we deliver creative solutions.
We create vertical isolated pods which has narrow but deep focus. We also create horizontal pods to collaborate and deliver sustainable outcomes.
We follow Agile methodologies to fail fast and deliver scalable and modular solutions. We constantly self-asses and realign to work with each customer in the most impactful manner.
Pre-requisites for the Role
1.Job ID-EMJR0120PS
- Primary skill:
- Java-spring boot-Hibernate
- Mysql
- CI/CD, Jenkins/Github (good to have)
- Junit/Mockito/testng
- Rest api
(Good to have)
Awards received in career
4.Years of Experience: 3-5 Years
- Location:(Hybrid)
- Position-19
- Budget- Max 14 LPA
- NP- Immediate
2. Data structure (HashMap, treemap, arraylist, linklist),
3. Streaming concepts (partitioning), Junit
4. Exception handling and workflow, Test coverage (why its important, how it gets handled at
java and spring layer, morckito library if the candidate knows that would be great),
5. OOPS concepts (inheritance),
6. Threading (mutex, threadpool, threading implementation, singleton factory, builder pattern,
abstract)
7. Real world problems (atleast 1 to be asked in IAAS interview) (movie ticket booking, parking
booking), To be asked to only selected candidates: Puzzle (probability/)
8. Memory management: Garbage Collection (GC), Heap dump, Thread dump, apache, google
library.
9. Spring frameworks and database. Data lakes, star lakes, schemas, indexing, partitioning,
optimize query, hibernate.
10. Data warehouse vs nosql vs time series database (KDB, DB2), data storage patterns.
11. Types of transaction control. Column level.
12. Query formation, grouping, nested queries, joints (inner joints, outer joints)
13. If candidate has spring exp: Architecture and various layers of Spring, coupling concepts,
dependency injections, inheritance, Bean level, JMS connection pooling concepts, Lambda,
Annotation vs XML, Kafka, Hibernates.
14. Good to have AI/ML inclination.
Bifurcation of Must have and good to have skills:
Must have skills Good to have skills
Core java (60%), spring (15%), and databases
(15%).
Mockito library
Data structure (HashMap, tree map, array list,
link list)
Threadpool
Streaming concepts (partitioning) Memory management
Exception handling Lambda, Annotation vs XML, Kafka, Hibernates
OOPS GCP or any cloud technology
Threading (singleton factory, builder pattern) AI/ML inclination
Real world problems (movie ticket booking,
parking booking)
Spring frameworks and database (indexing,
partitioning, layers of Spring, JMS connection)
Data warehouse vs NoSQL vs time series
database
Junit
Job description
- Design and develop large-scale business application using Java, Spring boot, Microservices Architecture
- Design and develop software application code by analyzing requirements and specification using Java and J2EE
- Creating webservices (SOAP/RESTful) and consuming webservices
- Strong fundamentals OOPS concepts, Exception Handling, Coding Standards
- Experience in MySQL/MSSQL/Oracle
- Experience in SDLC methodologies Agile / waterfall
- Good understanding of data structures and algorithms
- Basic working knowledge of Unix/Linux
- Must possess strong problem solving and troubleshooting skills
- Excellent team player with strong verbal & written communication skills.
Position - Software Development Engineer
Responsibilities
- Develop new user-facing features
- Build reusable code and libraries for future use
- Ensure the technical feasibility of API integrations
- Optimize application for maximum speed and scalability
- Collaborate with other team members and stakeholders
Requirements
- Proficient understanding of Java 8 or plus, Spring Frameworks, Spring Boot & Microservices
- Strong problem solving skills and good with product understanding
- Good understanding of server-side programming and integration with UI components.
- Good understanding of MySQL and any one NoSQL
- Good understanding of asynchronous request handling, partial page updates, and AJAX
- Proficient understanding of code repositories like git
- 2- 5 years of experience
Personal Characteristics
- Passion and commitment
- Coding enthusiastic
- High integrity
- Self-starter
Key Skills
- Java
- Spring
- Spring Boot
- J2EE
- should have at least 5 years of hands-on experience in backend software development using Java.
- should have proven expertise in Spring Boot REST/Microservices.
- should have used design patterns like MVP, MVC or MVVM and should know when to use which.
- should have working experience with relational and NoSQL databases.
- should have multiple years of experience with cloud application design and in one or more reputable cloud platform providers (e.g. AWS, GCP, Microsoft Azure … )
- should have professional experience working in an agile development environment.
- should have strong communication skills and like making decisions.
- should follow good software engineering principles such as TDD, writing modular, maintainable and clean code
Locus is a global decision- making platform in the supply chain that uses deep learning and proprietary algorithms to provide route optimization, real-time tracking, insights and analytics, beat optimization, efficient warehouse management, vehicle allocation and utilization, intuitive 3D packing and measurement of packages. Locus automates human decisions required to transport a package or a person, between any two points on earth, delivering gains along efficiency, consistency, and transparency in operations.
Locus, which has achieved a peak of 1 million orders processed in a day (200,000 orders an hour) and is trained & tested on over 100 million+ order deliveries, works in 75 cities across the globe. Locus works with several large-scale market leaders like Urban Ladder, Tata Group of Companies, Droplet, Licious, Rollick, Lenskart, other global FMCG, pharma, e-commerce, 3PL and logistics conglomerates.
Locus is backed by some of the biggest names in the market and recently raised $22 MN in Series B funding and also $4 Mn in a pre-Series B round. Earlier, In 2016, Locus raised $2.75 Mn (INR 18.3 Cr) in a Series A funding.
Locus was started by Nishith Rastogi and Geet Garg, two ex-Amazon engineers on a mission to democratize logistics intelligence for businesses across industries. Nishith was profiled by Forbes Asia in their ’30 Under 30’ 2018 list. Geet, on the other hand, holds a dual degree (BTech and MTech) in Computer Science and Engineering from the Indian Institute of Technology. Our team constitutes of engineers from Indian Institute of Technology and Birla Institute of Technology & Science- Pilani, and Data Scientists with PhDs from Carnegie Mellon University and Tata Institute of Fundamental Research. Our multifaced product and business team is led by senior members from Barclays, Google & Goldman Sachs with immense operational execution experience.
Job Description
- Design & implement backend APIs at Locus.sh
- Mentor junior developers technically.
- Actively work to reduce tech debt in the Locus backend
- Work towards more stability & scalability of the backend
- Tech stack - Java, AWS, Aurora etc.
Eligibility
- 4-8 years of product company experience
- OOP implementation experience. Programming language does not matter, We use Java internally but have hired folks from non Java background.
- Hands on experience in SQL, Dynamo DB, Postgres etc preferred.
- Prior experience building REST APIs
- Advanced understanding of AWS stack
- Prior knowledge of solving problems at scale.
Perks:
- Healthy catered meals at office
- You decide your own Work From Home (WFH) and Out Of Office (OOO)
- Pet-friendly - bring your pets to the office any day. Locus family already has a Rottweiler and a Beagle









