Engineering Manager

Bidgely, Inc; India; In loco; INR 4.000.000 - 7.000.000; Tempo pieno

Descrizione del lavoro

Bidgely, Inc. seeks a seasoned Engineering Manager to lead and grow a high-performing full-stack team building cloud-native applications.

You'll bridge technical execution and leadership, mentor engineers across backend, frontend, GenAI, MLOps, and data platforms, and drive delivery, architecture, and AI-enabled product features with a focus on reliability, security, and scalable practices. Strong stakeholder communication and strategic thinking are essential to navigate rapid growth and

Competenze

• Bachelor's in Computer Science, Software Engineering, or related field (Master's a plus).
• Minimum 8 years software engineering experience, with 2-4 as Engineering Manager or Tech Lead Manager.
• Proficient as a full stack engineer: Java, Spring Boot, Spark, React JS, and Python (additional language experience a plus).
• Experience managing and growing engineering teams (5-15 engineers).
• Track record of delivering complex multi-team software projects.
• Cloud-native application experience (AWS, Azure, GCP).
• Strong project management, Agile/Scrum, and stakeholder management skills.
• Preferred: Hands-on LLM API integration, agentic workflows, or AI/ML in product engineering.
• Preferred: Experience in regulated industries or enterprise SaaS.
• Proven ability to read/decode legacy codebases (JAR/WAR, monolithic) and lead migration to containerized microservices (Docker, Kubernetes).
• Deep understanding of event-driven and distributed systems, messaging, queuing, consistency, and fault tolerance.
• Highly motivated self-starter; fills process gaps proactively.
• Hands-on proficiency with Jira and Confluence for sprint ceremonies, backlog, and documentation standards.

Mansioni

• Lead, manage, and grow a full stack engineering team focused on technical quality, ownership, and collaboration.
• Conduct regular 1:1s, feedback, and growth plans for team members.
• Foster curiosity, accountability, psychological safety, and learning.
• Recruit, interview, and onboard new engineering talent.
• Shield the team from distractions while aligning with business goals.
• Recognize technical achievements and enable engineers’ best work.
• Provide technical guidance across backend (Java, Python), frontend, APIs, and data layers.
• Drive architectural decisions for scalable, maintainable cloud-based systems.
• Enforce engineering standards: code quality, testing, documentation, peer review.
• Lead design reviews, ensuring solutions are performant, secure, and production-ready.
• Stay up to date with evolving full stack tech and evaluate new tools for the stack.
• Address technical debt strategically.
• Modernize legacy codebases and lead re-platforming to containerized AWS deployments.
• Enforce SOLID principles, design patterns, and best practices.
• Conduct code reviews and provide senior-level support as required.
• Mentor both junior and senior engineers, bridging skill gaps and guiding problem-solving.

Conoscenze

Leadership

Full stack engineer

Java

Python

React JS

Spring Boot

Spark

Docker/Kubernetes

Cloud platforms

AI/LLM in product engineering

Formazione

Bachelor's in Computer Science, Software Engineering, or related field

Master's degree a plus

Strumenti

Jira

Confluence

Datadog

Prometheus

ELK Stack

Docker

Kubernetes

OpenAI API

Descrizione del lavoro

• Role Overview

  • Lead and grow a high-performing engineering team building and operating Bidgely's cloud-native applications and services.

  • Bridge technical execution and organizational leadership, ensuring scalable, reliable, and impactful product delivery.

  • Requires strong technical expertise in backend development (Java, Python, Agentic AI) with frontend familiarity, plus leadership skills to inspire and manage the team.

  • Serve as a "player-coach," stepping in to code, unblock deployments, decode legacy systems, and mentor engineers as needed.

  • Proactively identify team needs and actions, rather than waiting for instruction.

  • Report to the Head of Data Engineering.

  • Responsibilities include leading and mentoring engineers across backend, frontend, GenAI, MLOps, and Data platform layers.

  • Own end-to-end delivery of engineering initiatives for Bidgely's cloud application stack.

  • Drive technical strategy, architecture, and engineering best practices.

  • Manage project delivery, sprint planning, roadmap execution, and stakeholder communication.

  • Champion adoption of AI, LLM, and Agentic AI within products and engineering workflows.

  • Collaborate with Product, Data Science, Infrastructure, and QA to deliver high-quality solutions.

  • Foster a culture of ownership, continuous improvement, and psychological safety.

  • Drive migration from legacy code (JAR/WAR) to containerized, cloud-native microservices.

  • Manage workflows using Jira and Confluence for sprint hygiene and documentation.

  • Combine deep technical engagement with people leadership.

• Key Responsibilities

  • Engineering Leadership & People Management

    • Lead, manage, and grow a full stack engineering team focused on technical quality, ownership, and collaboration.

    • Conduct regular 1:1s, give feedback, and create growth plans for team members.

    • Foster a culture of curiosity, accountability, psychological safety, and learning.

    • Recruit, interview, and onboard new engineering talent.

    • Shield the team from distractions while aligning with business goals.

    • Recognize technical achievements and enable engineers’ best work.

  • Full Stack Technical Leadership

    • Provide technical guidance across backend (Java, Python), frontend, APIs, and data layers.

    • Drive architectural decisions for scalable, maintainable cloud-based systems.

    • Enforce engineering standards: code quality, testing, documentation, peer review.

    • Lead design reviews, ensuring solutions are performant, secure, and production-ready.

    • Stay up to date with evolving full stack tech and evaluate new tools for the stack.

    • Address technical debt strategically.

    • Modernize legacy codebases and lead re-platforming to containerized AWS deployments.

    • Enforce SOLID principles, design patterns, and best practices.

    • Conduct code reviews and provide senior-level support as required.

    • Mentor both junior and senior engineers, bridging skill gaps and guiding problem-solving.

  • Project & Delivery Management

    • Own engineering project delivery from scoping to post-launch monitoring.

    • Lead sprint planning, backlog grooming, and milestone tracking.

    • Identify and resolve risks, dependencies, and blockers proactively.

    • Maintain clear communication with leadership and stakeholders on delivery status.

    • Improve delivery velocity through process optimization, automation, and tooling enhancements.

  • Cloud-Native Application Development

    • Guide development and operation of full stack applications on cloud platforms (AWS, Azure, GCP).

    • Ensure best practices in microservices, containerization, CI/CD, and infrastructure-as-code.

    • Partner with Infrastructure for defining service contracts and operational standards.

    • Drive observability: structured logging, tracing, and alerting.

    • Ensure services meet reliability, scalability, and security standards.

  • AI, LLM & Agentic AI Enablement

    • Champion AI/LLM adoption in workflows: code generation, testing automation, productivity tools.

    • Collaborate with Data Science and Product teams for LLM-powered product features.

    • Guide responsible adoption of AI-assisted dev practices.

    • Stay updated on generative AI, LLM frameworks (LangChain, Strands), Agentic AI architectures.

    • Ensure engineering readiness for AI-powered product capabilities.

  • Cross-Functional Collaboration

    • Serve as main engineering liaison with Product, Data Science, Design, QA, and Infrastructure teams.

    • Participate in roadmap planning and provide engineering input for product decisions.

    • Support customer-facing technical discussions.

    • Collaborate with security on application-layer security standards.

  • Engineering Execution & Tooling

    • Own Jira and Confluence for sprint management and documentation.

    • Ensure engineers have clear task and priority visibility and acceptance criteria.

    • Drive continuous improvement via retrospectives, sprint reviews, and capacity planning.

• Success Metrics

  • Team Health & Growth

    • High team engagement, retention, and satisfaction levels.

    • Growth plans for all engineers with measured progress.

    • Effective, on-schedule hiring of top engineering talent.

  • Engineering Delivery

    • On-time, high-quality delivery of sprint and quarterly commitments.

    • Reduction in escaped defects and production incidents.

    • Improvement in lead time, cycle time, and deployment frequency.

  • Technical Excellence

    • Improvement in codebase health metrics (test coverage, code reviews, documentation).

    • Adoption of AI/LLM-enabled development tools for improved productivity.

    • Engineering systems meeting reliability, scalability, and security targets.

• Qualifications & Experience

  • Education: Bachelor's in Computer Science, Software Engineering, or related field (Master's a plus).

  • Minimum 8 years software engineering experience, with 2-4 as Engineering Manager or Tech Lead Manager.

  • Proficient as a full stack engineer: Java, Spring Boot, Spark, React JS, and Python (additional language experience a plus).

  • Experience managing and growing engineering teams (5-15 engineers).

  • Track record of delivering complex multi-team software projects.

  • Cloud-native application experience (AWS, Azure, GCP).

  • Strong project management, Agile/Scrum, and stakeholder management skills.

  • Preferred: Hands-on LLM API integration, agentic workflows, or AI/ML in product engineering.

  • Preferred: Experience in regulated industries or enterprise SaaS.

  • Proven ability to read/decode legacy codebases (JAR/WAR, monolithic) and lead migration to containerized microservices (Docker, Kubernetes).

  • Deep understanding of event-driven and distributed systems, messaging, queuing, consistency, and fault tolerance.

  • Highly motivated self-starter; fills process gaps proactively.

  • Hands-on proficiency with Jira and Confluence for sprint ceremonies, backlog, and documentation standards.

• Technical & Domain Expertise

  • Strong backend proficiency: Java (Spring Boot, microservices), Python (FastAPI, Flask, or equivalent).

  • Solid frontend and API design skills (React, Angular, REST, GraphQL).

  • Experience with cloud-native patterns: containerization, CI/CD, serverless architectures.

  • Familiar with relational/NoSQL databases, data modeling, and optimization.

  • Working knowledge of cloud platforms, deployment models, and cost management.

  • Understanding of software security, authentication/authorization and OWASP best practices.

  • Exposure to AI/ML and LLM frameworks (LangChain, LlamaIndex, OpenAI API); agentic AI architectures is a strong advantage.

  • Familiarity with observability tools (Datadog, Prometheus, ELK Stack).

  • Experience with legacy Java app packaging, deployment, and migration to containers.

  • Command of SOLID principles, design patterns (GoF), distributed architecture, message brokers (Kafka, RabbitMQ), and orchestration.

• Core Competencies

  • Deep technical skill with leadership experience.

  • People-first leadership, promoting growth and best work.

  • Ownership of delivery, removing blockers proactively.

  • AI & LLM fluency for engineering and product integration.

  • Ability to translate technical complexity for cross-functional stakeholders.

  • Growth mindset, continuous learning, comfortable with ambiguity.

• Why Join Bidgely?

  • Shape the future of clean energy and sustainability.

  • Work in a fast-paced, diverse, cross-functional environment.

  • Competitive pay, benefits, and growth opportunities.

  • Make an impact at the intersection of AI, data, and climate tech.

• Diversity, Equity, Inclusion and Equal Opportunity

  • Bidgely values unique backgrounds, perspectives, and abilities to benefit the company, clients, and community.

  • Commitment to an inclusive workplace where all can grow and contribute.