Senior BDA

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.

Data - AI / ML Engineer 

Full-Time   |   On-site, Kolkata   |   Immediate Joining   |   4+ years experience

ABOUT US 

Company Name: Freeflow ventures

We are a venture building and investment firm focused on emerging markets across India, the Middle East, and Africa. We work with early-stage startups -diagnosing gaps, structuring interventions, and preparing them for investor-readiness through a proprietary data and intelligence platform.

Our platform combines automated data verification, startup scoring, and structured workflow automation to bring consistency and credibility to early-stage investment decisions. We are at an active build and expansion phase, and this role sits at the core of that infrastructure.

ROLE OVERVIEW

We are looking for a Data - AI / ML Engineer who can own both the data pipelines that bring verified information into our platform and the intelligence models that turn that information into reliable startup scores.

This is a dual-responsibility role. You will be expected to build and maintain robust data infrastructure as well as develop, calibrate, and improve machine learning models. Both are equally important to the platform.

You will work closely with the Platform Owner and alongside a Backend Engineer who owns system integrations and workflow logic. Your work produces the scored intelligence output. The Backend Engineer's work connects that output to platform actions. The two roles are tightly interdependent and require close daily collaboration, especially in the first 30 days.

Note: You are the first technical hire on the platform team. The Backend Engineer joins the same week. Clear communication, well-defined handoff points, and shared documentation between the two of you are non-negotiable from Day 1.

WHAT YOU WILL DO

Data Pipeline

• Build and maintain pipelines that collect, clean, and normalize data from multiple external sources into a consistent, usable format
• Design connector architecture that allows individual data sources to be added, swapped, or removed without rebuilding the entire pipeline
• Implement automated data quality checks that catch bad data before it reaches the scoring layer -anomaly detection, constraint enforcement, and schema validation
• Build an automated eligibility screening system that verifies whether a startup has sufficient verified data before assessment begins
• Ensure the pipeline is resilient -critical data signals must have backup sources so a single vendor failure does not disrupt platform output
• Structure data storage to support different regulatory requirements across multiple countries -data from different regions must be handled according to the rules of that region

AI and Machine Learning

• Audit the existing scoring engine before making any changes -understand what it does, how it was built, and what would be lost if it were modified
• Calibrate scoring models against real portfolio data so that scores are meaningful, consistent, and comparable across different startup types and stages
• Build confidence scoring logic that determines when the system is certain enough to act autonomously and when it should route to human review
• Ensure every model output is explainable -investors must be able to see exactly which data points drove a score, not just the final number
• Build a feedback loop so that real-world outcomes feed back into the model over time, making it progressively more accurate
• Maintain a structured data store of assessment outputs and outcomes that the model uses to improve

Working With the Backend Engineer

• Define a clear data contract at the handoff point -what data you produce, in what format, and what the Backend Engineer can expect to receive
• Collaborate on trigger logic -what score thresholds or confidence drops should fire what system actions
• Align on data schema requirements so that the APIs the Backend Engineer builds conform to the structure your pipeline produces
• Communicate blockers early -the pipeline and backend system are built simultaneously, so delays on one side directly affect the other
• Document everything you build so the Backend Engineer and Platform Owner can understand, debug, and extend it without depending on you for every question

WHAT WE ARE LOOKING FOR

Skills are divided into two categories. Must Have means the role cannot function without it. Good to Have means it gives you an edge.

Skill

Priority

Data Engineering

Building and maintaining data pipelines from multiple sources

Must Have

Data normalization and schema design

Must Have

Automated data quality validation

Must Have

API integration across different source types

Must Have

Pipeline orchestration and scheduling

Must Have

Cloud infrastructure -storage, compute, and deployment

Must Have

Version control and code documentation

Must Have

AI and Machine Learning

Building and calibrating supervised machine learning models

Must Have

Model explainability -making model outputs traceable and interpretable

Must Have

Confidence scoring and threshold calibration

Must Have

Experiment tracking and model versioning

Must Have

Building feedback loops that improve models over time using real-world outcomes

Must Have

Natural language processing or document understanding

Good to Have

Vector databases and semantic search

Good to Have

Collaboration and Context

Ability to define clear data contracts and handoff points with backend engineers

Must Have

Clear written documentation of pipeline logic, model decisions, and failure modes

Must Have

Prior experience working in or with early-stage startups

Good to Have

Exposure to financial data, investment platforms, or data verification systems

Good to Have

WHAT WE OFFER

• Competitive compensation based on experience -discussed during the interview process
• Ownership of both the data and intelligence layers from Day 1 -this is not a support or maintenance role
• Direct access to the Platform Owner and Founder 
• Close collaboration with a Backend Engineer from Day 1 -the two roles are designed to work as a unit
• Work on a genuinely novel problem in an emerging market context
• On-site Kolkata with a small, high-accountability team
• Opportunity to scale the platform across multiple international markets

Position Title : Senior Data Engineer(Founding Member) - Insurtech StartUp

Location : Hyderabad(Onsite)

Immediate to 15 days Joiners

Experience : 5+ to 13 Years

Role Summary

We are looking for a Senior Data Engineer who will play a foundational role in:

• Client onboarding from a data perspective
• Understanding complex insurance data flows
• Designing secure, scalable ingestion pipelines
• Establishing strong data modeling and governance standards

This role sits at the intersection of technology, data architecture, security, and business onboarding.

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Key Responsibilities

• Lead end-to-end data onboarding for new clients and partners, working closely with business and product teams to understand client systems, data formats, and migration constraints
• Define and implement data ingestion strategies supporting multiple sources and formats, including CSV, XML, JSON files, and API-based integrations
• Design, build, and operate robust, scalable ETL/ELT pipelines, supporting both batch and near-real-time data processing
• Handle complex insurance-domain data including Contracts, Claims, Reserves, Cancellations, and Refunds
• Architect ingestion pipelines with security-by-design principles, including secure credential management (keys, secrets, tokens), encryption at rest and in transit, and network-level controls where required
• Enforce role-based and attribute-based access controls, ensuring strict data isolation, tenancy boundaries, and stakeholder-specific access rules
• Design, maintain, and evolve canonical data models that support operational workflows, reporting & analytics, and regulatory/audit requirements
• Define and enforce data governance standards, ensuring compliance with insurance and financial data regulations and consistent definitions of business metrics across stakeholders
• Build and operate data pipelines on a cloud-native platform, leveraging distributed processing frameworks (Spark / PySpark), data lakes, lakehouses, and warehouses
• Implement and manage orchestration, monitoring, alerting, and cost-optimization mechanisms across the data platform
• Contribute to long-term data strategy, platform architecture decisions, and cost-optimization initiatives while maintaining strict security and compliance standards

Required Technical Skills

• Core Stack: Python, Advanced SQL(Complex joins, window functions, performance tuning), Pyspark
• Platforms: Azure, AWS, Data Bricks, Snowflake
• ETL / Orchestration: Airflow or similar frameworks
• Data Modeling: Star/Snowflake schema, dimensional modeling, OLAP/OLTP
• Visualization Exposure: Power BI
• Version Control & CI/CD: GitHub, Azure Devops, or equivalent
• Integrations: APIs, real-time data streaming, ML model integration exposure

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
• 5+ years of experience in data engineering or similar roles
• Strong ability to align technical solutions with business objectives
• Excellent communication and stakeholder management skills

What We Offer

• Direct collaboration with the core US data leadership team
• High ownership and trust to manage the function end-to-end
• Exposure to a global environment with advanced tools and best practices

• Contribute to all stages of the software development lifecycle
• Design, implement and maintain Java-based applications that can be high-volume and low-latency
• Analyze user requirements to define business objectives
• Envisioning system features and functionality
• Define application objectives and functionality
• Ensure application designs conform with business goals

Responsibilities:

• Develop and maintain scalable web applications using the MERN stack.
• Design and implement responsive user interfaces with React.
• Build server-side logic using Node.js and Express.js.
• Manage and optimize databases using MongoDB.
• Integrate third-party services and APIs.
• Write clean, maintainable, and efficient code.
• Collaborate with front-end and back-end teams to ensure smooth development processes.

• 4+ yearsof working experienceas a PHP developer
• User authentication and authorization between multiple systems, servers, and environments
• Experience with PHP web frameworks including CodeIgniter and Cake
• Proficient knowledge of web technologies including HTML, CSS, JavaScript, jQuery, AJAX, etc.
• Experience with building restful JSON web services.
• Ability to manage projects.
• Familiarity with SQL, PostgreSQL databases
  
  

Responsibilities

• PHP developer who will play a key role in our web development projects.
• Design and develop the front end of the website and its architecture.
• Design and manage the website’s back end, including database and server integration.
• Contribute to all phases of the development lifecycle
• Modify or improve existing websites to make them more interactive and engaging.
• Solve complex performance problems and architectural challenges

Additional Skills

• Good knowledge ofjs, APIs, and Google mapsis a plus.
• Strong analytical, problem-solving, and troubleshooting skills.

We are searching for a highly-creative digital marketing manager to lead our marketing team. In this position, you will be responsible for all aspects of our marketing operations. Your central goal is to help grow our brand’s influence locally while also increasing brand loyalty and awareness.

Your duties will include planning, implementing, and monitoring our digital marketing campaigns across all digital networks. Our ideal candidate is someone with experience in marketing, art direction, and social media management. In addition to being an outstanding communicator, you will also demonstrate excellent interpersonal and analytical skills.

• Design and oversee all aspects of our digital marketing team including our marketing database, email, and display advertising campaigns.
• Develop and monitor campaign budgets.
• Plan and manage our social media platforms.
• Prepare accurate reports on our marketing campaign’s overall performance.
• Coordinate with advertising and media experts to improve marketing results.
• Identify the latest trends and technologies affecting our industry.
• Evaluate important metrics that affect our website traffic, service quotas, and target audience.
• Work with the team to brainstorm new and innovative growth strategies.
• Oversee and manage all contests, giveaways, and other digital projects.

Desired Candidate Profile

Mentor To Go is an android and web based platform to help students improve their work readiness through self-learning sessions, personalised mentorship provided by mentor professionals from a range of careers, and work experience opportunities.

The technology platform implements  functionalities such as: screening surveys of mentors and mentees, training content for mentors, matching through an algorithm, and mentorship through the delivery of structured activities. 

The application technology architecture comprises of the following:

o   a Python Django web application with NGinx and Gunicorn

o   PostgreSQL database

o   A React Android and Web app

o   Rest APIs which interact between the Android app and the Django webserver

Our vision at Mentor To Go is to provide career mentorship to young people anywhere, anytime across the length and breadth of India.

We are looking for a backend software developer who is passionate about using web technologies to solve social problems and creating experiences that are elegant and effective. You will own the back end development of features of the Mentor To Go platform from conceptualisation through design and testing, working closely with other developers, the technical project manager, and the program operations team. You are user-centric, continuously demonstrate strategic & analytical abilities, and are laser focused on executing at speed. You must have the ability to succeed in a fast paced environment, where success is dependent on your ability to collaborate with cross-functional team members in a positive, productive, and transparent way.

Minimum requirements 

• Bachelor’s degree in engineering preferably  CS  or related discipline  
• 3+ years experience working in Unix/Linux environments building web and mobile applications
• Proficiency in developing and deploying cloud based Python/Postgresql applications preferably using frameworks such as Django
• Experience with design and development of moderately complex software projects
• Strong written and oral communication skills
• Familiarity with version control software such as Git

Desired  requirements 

• 5+ years of overall relevant work experience
• Experience building apps using React/React-Native
• Basic understanding of AWS cloud
• Ability to participate in technical discussions and help make technical trade-offs

About Mentor Together

https://mentortogether.org/">Mentor Together is India’s first and largest youth mentoring  non-profit organization with a mission to facilitate empowering mentoring relationships and networks that help young people break the inequalities of opportunity and actualise their potential.

http://bit.ly/mentortogo">Mentor To Go is the world’s first mobile mentoring platform created by Mentor Together with the support of Cisco India, LinkedIn Social Impact, British Telecom and Sterlite Technologies.