Java Developer

Who we are: My AI Client is building the foundational platform for the "agentic economy," moving beyond simple chatbots to create an ecosystem for autonomous AI agents and they aim to provide tools for developers to launch, manage, and monetize AI agents as "digital coworkers."

The Challenge

The current AI stack is fragmented, leading to issues with multimodal data, silent webhook failures, unpredictable token usage, and nascent agent-to-agent collaboration. My AI Client is building a unified, robust backend to resolve these issues for the developer community.

Your Mission

As a foundational member of the backend team, you will architect core systems, focusing on:

• Agent Nervous System: Designing agent-to-agent messaging, lifecycle management, and high-concurrency, low-latency communication.
• Multimodal Chaos Taming: Engineering systems to process and understand real-time images, audio, video, and text.
• Bulletproof Systems: Developing secure, observable webhook systems with robust billing, metering, and real-time payment pipelines.

What You'll Bring

• My AI Client seeks an experienced engineer comfortable with complex systems and ambiguity.

Core Experience:

● Typically 3 to 5 years of experience in backend engineering roles.

● Expertise in Python, especially with async frameworks like FastAPI.

● Strong command of Docker and cloud deployment (AWS, Cloud Run, or similar).

● Proven experience designing and building microservice or agent-based architectures.

Specialized Experience (Ideal):

• Real-Time Systems: Experience with real-time media transmission like WebRTC, WebSockets and ways to process them.
• Scalable Systems: Experience in building scalable, fault-tolerant systems with a strong understanding of observability, monitoring, and alerting best practices.
• Reliable Webhooks: Knowledge of scalable webhook infrastructure with retry logic, backoffs, and security.
• Data Processing: Experience with multimodal data (e.g., OCR, audio transcription, video chunking with FFmpeg/OpenCV).
• Payments & Metering: Familiarity with usage-based billing systems or token-based ledgers.

Your Impact

• The systems designed by this role will form the foundation for:
• Thousands of AI agents for major partners across chat, video, and APIs.
• A new creator economy enabling developers to earn revenue through agents.
• The overall speed, security, and scalability of my client’s AI platform.

Why Join Us?

• Opportunity to solve hard problems with clean, scalable code.
• Small, fast-paced team with high ownership and zero micromanagement.
• Belief in platform engineering as a craft and care for developer experience.
• Conviction that AI agents are the future, and a desire to build their powering platform.
• Dynamic, collaborative in-office work environment in Bengaluru in a Hybrid setup (weekly 2 days from office)
• Meaningful equity in a growing, well-backed company.
• Direct work with founders and engineers from top AI companies.
• A real voice in architectural and product decisions.
• Opportunity to solve cutting-edge problems with no legacy code.

Ready to Build the Future?

My AI Client is building the core platform for the next software paradigm. Interested candidates are encouraged to apply with their GitHub, resume, or anything that showcases their thinking.

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.

5–10 years of experience in backend or full-stack development (Java, C#, Python, or Node.js preferred).

•Design, develop, and deploy full-stack web applications (front-end, back-end, APIs, and databases).

•Build responsive, user-friendly UIs using modern JavaScript frameworks (React, Vue, or Angular).

•Develop robust backend services and RESTful or GraphQL APIs using Node.js, Python, Java, or similar technologies.

•Manage and optimize databases (SQL and NoSQL).

•Collaborate with UX/UI designers, product managers, and QA engineers to refine requirements and deliver solutions.

•Implement CI/CD pipelines and support cloud deployments (AWS, Azure, or GCP).

•Write clean, testable, and maintainable code with appropriate documentation.

•Monitor performance, identify bottlenecks, and troubleshoot production issues.

•Stay up to date with emerging technologies and recommend improvements to tools, processes, and architecture.

•Proficiency in front-end technologies: HTML5, CSS3, JavaScript/TypeScript, and frameworks like React, Vue.js, or Angular.

•Strong experience with server-side programming (Node.js, Python/Django, Java/Spring Boot, or .NET).

•Experience with databases: PostgreSQL, MySQL, MongoDB, or similar.

•Familiarity with API design, microservices architecture, and REST/GraphQL best practices.

•Working knowledge of version control (Git/GitHub) and DevOps pipelines.

Understanding of cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).

Job Title: Java Backend Developer

Experience: ~3-6 years (Mid-to-Senior)

Employment Type: Full-time, Permanent

Location : Bangalore

Role Overview

As a Java Backend Developer, you’ll be responsible for designing, developing, and maintaining scalable backend systems and microservices. You’ll work with cross-functional teams to build high-performance distributed services, APIs, and data-driven applications that power business solutions.

Key Responsibilities

• Design and implement microservices and backend components using Java (8+) and Spring Boot.
• Build and consume RESTful APIs and integrate with internal/external services.
• Work with event-driven systems and messaging using Apache Kafka (producers/consumers).
• Develop and optimize databases, including SQL (e.g., MySQL/PostgreSQL) and NoSQL (e.g., MongoDB/Cassandra).
• Participate in CI/CD pipelines, automated builds, and deployments using tools like Git, Maven, Jenkins.
• Ensure code quality through unit and integration testing, documentation, and code reviews.
• Collaborate with frontend developers, QA, DevOps, and product teams following Agile methodologies.

Required Skills & Qualifications

• Bachelor’s degree in Computer Science, Information Technology, or related field.
• Proven hands-on experience with Core Java and Spring Boot development.
• Strong understanding of microservices architecture, REST APIs, and distributed systems.
• Experience with message queues/event streaming (Apache Kafka).
• Skilled in relational and NoSQL databases and writing optimized queries.
• Comfortable with CI/CD tools (e.g., Git, Maven, Jenkins) and version control.
• Good problem-solving, debugging, and collaboration skills.

Preferred / Nice-to-Have

• Cloud platform experience (AWS / Azure / GCP).
• Familiarity with containerization (Docker) and orchestration (Kubernetes).
• Knowledge of performance tuning, caching strategies, observability (metrics/logging).
• Agile/Scrum development experience.

Required Skills:

• 2+ year of experience in Development in JAVA technology.
• Strong Java Basics
• SpringBoot or Spring MVC
• Hands on experience on Relational Databases (SQL query or Hibernate) + Mongo (JSON parsing)
• Proficient in REST API development
• Messaging Queue (RabitMQ or Kafka)
• Microservices
• Any Caching Mechanism
• Good at problem solving

Good to Have Skills:

• 4+ years of experience in using Java/J2EE tech stacks
• Good understanding of data structures and algorithms.
• Excellent analytical and problem solving skills.
• Ability to work in a fast paced internet start-up environment.
• Experience in technical mentorship/coaching is highly desirable.
• Understanding of AI/ML algorithms is a plus.

Desired Candidate Profile

• A team focus with strong collaboration and communication skills
• Exceptional ability to quickly grasp high-level business goals, derive requirements, and translate them into effective technical solutions
• Exceptional object-oriented thinking, design and programming skills (Java 8 or 11)
• Expertise with the following technologies : Data Structures, Design Patterns ,Code Versioning Tools(Github/bitbucket/..), XML, JSON, Spring Batch Restful, Spring Cloud, Grafana(Knowledge/Experience), Kafka, Spring Boot, Microservices, DB/NoSQL, Docker, Kubernetes, AWS/GCP, Architecture design (Patterns) Agile, JIRA.
• Penchant toward self-motivation and continuous improvement; these words should describe you: dedicated, energetic, curious, conscientious, and flexible.

• Creating, designing and developing data models
• Prepare plans for all ETL (Extract/Transformation/Load) procedures and architectures
• Validating results and creating business reports
• Monitoring and tuning data loads and queries
• Develop and prepare a schedule for a new data warehouse
• Analyze large databases and recommend appropriate optimization for the same
• Administer all requirements and design various functional specifications for data
• Provide support to the Software Development Life cycle
• Prepare various code designs and ensure efficient implementation of the same
• Evaluate all codes and ensure the quality of all project deliverables
• Monitor data warehouse work and provide subject matter expertise
• Hands-on BI practices, data structures, data modeling, SQL skills

Hard Skills for a Data Warehouse Developer:

• Hands-on experience with ETL tools e.g., DataStage, Informatica, Pentaho, Talend
• Sound knowledge of https://www.freelancermap.com/it-projects/sql-1084" target="_blank">SQL
• Experience with SQL databases such as Oracle, DB2, and SQL
• Experience using Data Warehouse platforms e.g., SAP, Birst
• Experience designing, developing, and implementing Data Warehouse solutions
• Project management and system development methodology
• Ability to proactively research solutions and best practices

Soft Skills for Data Warehouse Developers:

• Excellent Analytical skills
• Excellent verbal and written communications
• Strong organization skills
• Ability to work on a team, as well as independently

As a Senior Software Engineer - I,you'll take on complex problems that span multiple components and teams. As SSE - I, you could expect to: 

• Independently own one or more multiple modules, which includes: requirement analysis, design, development, maintenance & support
• Write extensive, efficient code to address complex modules and that handles interaction between multiple components. 
• Rapidly iterate to add new functionalities and solves complex problems with simple and intuitive solutions
• Produce architecture with clean interfaces, that are efficient and scalable
• Participate and contribute to architectural discussions
• Perform design and code reviews
• Perform technical feasibility and trade off studies & guides others to perform these studies
• Solve production issues. Investigate and provide solutions to minimize the business impact due to outage
• Continuously improve performance metrics of modules you own.
• Actively mentor and develop junior developers in all software development practices
• Participate in the hiring process (referrals, interviews, attending recruiting events or writing blogs)
• Onboard and mentors new team members, helps shape the culture of the team
• Collaborate effectively across teams to solve problems, execute and deliver results

Minimum Requirements: 

• A minimum of 4 years of relevant software development experience