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Responsible for developing, enhancing, modifying, and maintaining chatbot applications in the Global Markets environment. The role involves designing, coding, testing, debugging, and documenting conversational AI solutions, along with supporting activities aligned to the corporate systems architecture.

You will work closely with business partners to understand requirements, analyze data, and deliver optimal, market-ready conversational AI and automation solutions.

Key Responsibilities

• Design, develop, test, debug, and maintain chatbot and virtual agent applications
• Collaborate with business stakeholders to define and translate requirements into technical solutions
• Analyze large volumes of conversational data to improve chatbot accuracy and performance
• Develop automation workflows for data handling and refinement
• Train and optimize chatbots using historical chat logs and user-generated content
• Ensure solutions align with enterprise architecture and best practices
• Document solutions, workflows, and technical designs clearly

Required Skills

• Hands-on experience in developing virtual agents (chatbots/voicebots) and Natural Language Processing (NLP)
• Experience with one or more AI/NLP platforms such as:
• Dialogflow, Amazon Lex, Alexa, Rasa, LUIS, Kore.AI
• Microsoft Bot Framework, IBM Watson, Wit.ai, Salesforce Einstein, Converse.ai
• Strong programming knowledge in Python, JavaScript, or Node.js
• Experience training chatbots using historical conversations or large-scale text datasets
• Practical knowledge of:
• Formal syntax and semantics
• Corpus analysis
• Dialogue management
• Strong written communication skills
• Strong problem-solving ability and willingness to learn emerging technologies

Nice-to-Have Skills

• Understanding of conversational UI and voice-based processing (Text-to-Speech, Speech-to-Text)
• Experience building voice apps for Amazon Alexa or Google Home
• Experience with Test-Driven Development (TDD) and Agile methodologies
• Ability to design and implement end-to-end pipelines for AI-based conversational applications
• Experience in text mining, hypothesis generation, and historical data analysis
• Strong knowledge of regular expressions for data cleaning and preprocessing
• Understanding of API integrations, SSO, and token-based authentication
• Experience writing unit test cases as per project standards
• Knowledge of HTTP, REST APIs, sockets, and web services
• Ability to perform keyword and topic extraction from chat logs
• Experience training and tuning topic modeling algorithms such as LDA and NMF
• Understanding of classical Machine Learning algorithms and appropriate evaluation metrics
• Experience with NLP frameworks such as NLTK and spaCy

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:

Deqode is looking for a highly motivated and experienced Python + AWS Developer to join our growing technology team. This role demands hands-on experience in backend development, cloud infrastructure (AWS), containerization, automation, and client communication. The ideal candidate should be a self-starter with a strong technical foundation and a passion for delivering high-quality, scalable solutions in a client-facing environment.

Key Responsibilities:

• Design, develop, and deploy backend services and APIs using Python.
• Build and maintain scalable infrastructure on AWS (EC2, S3, Lambda, RDS, etc.).
• Automate deployments and infrastructure with Terraform and Jenkins/GitHub Actions.
• Implement containerized environments using Docker and manage orchestration via Kubernetes.
• Write automation and scripting solutions in Bash/Shell to streamline operations.
• Work with relational databases like MySQL and SQL, including query optimization.
• Collaborate directly with clients to understand requirements and provide technical solutions.
• Ensure system reliability, performance, and scalability across environments.

Required Skills:

• 3.5+ years of hands-on experience in Python development.
• Strong expertise in AWS services such as EC2, Lambda, S3, RDS, IAM, CloudWatch.
• Good understanding of Terraform or other Infrastructure as Code tools.
• Proficient with Docker and container orchestration using Kubernetes.
• Experience with CI/CD tools like Jenkins or GitHub Actions.
• Strong command of SQL/MySQL and scripting with Bash/Shell.
• Experience working with external clients or in client-facing roles.

Preferred Qualifications:

• AWS Certification (e.g., AWS Certified Developer or DevOps Engineer).
• Familiarity with Agile/Scrum methodologies.
• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management abilities.

We are seeking a highly skilled and motivated Python Developer with hands-on experience in AWS cloud services (Lambda, API Gateway, EC2), microservices architecture, PostgreSQL, and Docker. The ideal candidate will be responsible for designing, developing, deploying, and maintaining scalable backend services and APIs, with a strong emphasis on cloud-native solutions and containerized environments.

Key Responsibilities:

• Develop and maintain scalable backend services using Python (Flask, FastAPI, or Django).
• Design and deploy serverless applications using AWS Lambda and API Gateway.
• Build and manage RESTful APIs and microservices.
• Implement CI/CD pipelines for efficient and secure deployments.
• Work with Docker to containerize applications and manage container lifecycles.
• Develop and manage infrastructure on AWS (including EC2, IAM, S3, and other related services).
• Design efficient database schemas and write optimized SQL queries for PostgreSQL.
• Collaborate with DevOps, front-end developers, and product managers for end-to-end delivery.
• Write unit, integration, and performance tests to ensure code reliability and robustness.
• Monitor, troubleshoot, and optimize application performance in production environments.

Required Skills:

• Strong proficiency in Python and Python-based web frameworks.
• Experience with AWS services: Lambda, API Gateway, EC2, S3, CloudWatch.
• Sound knowledge of microservices architecture and asynchronous programming.
• Proficiency with PostgreSQL, including schema design and query optimization.
• Hands-on experience with Docker and containerized deployments.
• Understanding of CI/CD practices and tools like GitHub Actions, Jenkins, or CodePipeline.
• Familiarity with API documentation tools (Swagger/OpenAPI).
• Version control with Git.

Engineering Manager – Backend

Opportunity in this role / Why should you join us?

Series D funded supply chain startup.

Requirements

• Software engineering experience of greater than or equal to 7 years
• Experience managing a technical team of at least 3 people
• Exposure to consumer facing products
• Strong technical background and ability to contribute to design and review
• Familiarity with our tech stack or an analogous tech stack

Technologies Used

• Web application frameworks : Ktor, Spring Boot, Ruby on Rails, Node.js, Java Play, AWS Lambda
• Languages : Kotlin, Java, Ruby, Javascript, Python
• Datastores : PostgreSQL, Aerospike, Redis, DynamoDB, Amazon Redshift
• Communication : HTTP, Amazon SQS, Sidekiq, Amazon SNS
• Server management : Amazon ECS, Docker
• Design frameworks : Domain Driven Design, Clean Architecture, Layered Architecture

Roles and Responsibilities

This role requires a person to drive the engineering of a set of products by aligning with business and product

stakeholders and building and upskilling a team to aid in this. The responsibilities include:

Business and product alignment and planning

• Work closely with business and product stakeholders to understand and align with product initiatives and iterations.
• Help shape the engineering requirement by aligning with the product manager and fleshing out concepts and user flows.
• Formalize business requirements into roadmaps and sprints.

1. Product and system development

• Drive high level modeling and design for projects, also focusing on non-functional aspects, including but not limited to database design, communication protocols, deployment systems, etc.
• Drive adoption of design frameworks like domain driven design, clean architecture, etc., resulting in a robust layered architecture.
• Drive good code review practices, using the review process as a mentoring tool to upskill people.
• Ensure test coverage of systems, partly through unit and integration testing, and partly through blackbox testing by collaborating with the Quality Assurance team, via good testing practices.

1. Project Management

• Drive the execution of the project by delegating tasks effectively.
• Resolve blockers through technical expertise, negotiation and delegation.
• Estimate timelines and ensure adherence to them through effective sync-ups and course corrections.

1. Maintenance

• Formulate SLAs and oversee their adherence for the various systems, effectively tracking issues and performance inefficiencies.
• Performance monitoring and optimization for systems.
• Drive technical re-design, remodeling and refactoring of systems for robustness and sustainability.

1. Team Management

• Typically manage a team of 3 - 6 members and a portfolio of 3 - 6 products.
• Do periodic assessment of reportees, chart their career growth paths and train them.
• Recruit members into the team by collaborating effectively with the recruitment team.

Product Overview

You will be contributing to products concerning both customers and partner drivers. Product sectors

include:

• Growth : You’ll build tools to help boost user growth on the platform including our industry bestdriver on-boarding, training and certification system, referral system, and lead managementmmodels.
• Lifecycle Management : Build tools to help users engage with the platform better, which includes rewards and recognition module, subscription service, account management tools, partner and customer wallets and payout modules, and churn detection systems among others.
• Transaction Experience : You’ll help deliver the most delightful booking experience to our customers and drivers. As part of this team, you’ll be responsible for our core booking system, pricing and payment systems, location tracking and filtering services, fraud prevention systems, and in-app ticketing and support among others.
• Fulfilment : As part of the fulfilment team, you’ll work on systems which ensure high degree of ride fulfilment on the platform. Tools including allocation methodologies and system, dynamic pricing, dynamic partner routing, and partner re-activation tools among others.
• Enterprise Solutions : You’ll help Porter’s enterprise customers achieve delivery excellence. You’ll build tools for contract management, fleet management, fleet and route optimisation tools, alerting and monitoring tools, and analytics suite among others.

Hands on experience in Python in 2.x and 3.x versions

• Developed and deployed services in AWS serverless Architecture
• Developed REST API’s using serverless framework, AWS Lambda, API Gateway
• Developed queue and notification services using AWS components - SQS, SNS
• Implemented authorization and authentication using AWS Cognito pool
• Developed Facial recognition systems using AWS Rekognition
• Hands on experience in Flask, Tornado, Quartz framework
• Hands on experience in designing and working on MicroService & Monolithic architecture
• Basic understanding of front-end technologies HTML, CSS, JavaScript, jQuery

Mongo dB experience is must

GeoSpoc is looking for passionate backend developers who would like to solve complex business problems using location-aware data and cutting-edge tools and technologies such as microservices and cloud platforms such as AWS.

• A passionate developer with solid understanding of software basics  
• Always willing to learn and explore upcoming technologies
• Pro-active, reliable and result oriented
• Someone who can continuously perform in a fast-paced environment

• 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 or Pyramid)
• Knowledge of object-relational mapping (ORM)
• Familiarity with front-end technologies (like JavaScript and HTML5)

• Writing and testing code, debugging programs and integrating applications with third-party web services
• Work closely with small teams of designers, frontend developers, GIS experts as well as business stakeholders
• Own the development lifecycle of backend systems from design to deployment
• Go above and beyond to deliver great quality software solutions on time