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• Location – Mumbai
• Language: English, Hindi
• Good coordinating and communicating skill

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.

Strong Technical Recruiter profile

Mandatory (Experience 1): Must have 7+ years of experience in end to end recruitment (sourcing, screening, interviewing, offer negotiation, joining etc)

Mandatory (Experience 2): Must have 4+ years of experience in tech recruitment across different tech roles

Mandatory ( Tech Skill 1): Strong grasp of technical concepts and ability to evaluate candidate fit for different technical roles

Mandatory (Tech Skills 2): Must have experience of analyzing data to improve hiring funnel, take data-driven hiring decisions

Mandatory (Tech Skills 3): Must be proficient in advanced sourcing techniques such as Boolean search, social media recruiting, and referral programs

Mandatory (Communication): Excellent verbal and written communication skills — should be articulate, confident, and well-spoken in interactions

Mandatory (Company): Product companies

Mandatory (Note): This is an IC role

Job Description:

• Experience in Python (Only Backend), Data structures, Oops, Algorithms, Django, NumPy etc.

• Notice/Joining of not more than 30 days.

• Only Premium Institute- Tier 1 and Tier 2.

• Hybrid Mode of working.

• Good understanding of writing Unit Tests using PYTest.

• Good understanding of parsing XML’s and handling files using Python.

• Good understanding with Databases/SQL, procedures and query tuning.

• Service Design Concepts, OO and Functional Development concepts.

• Agile Development Methodologies.

• Strong oral and written communication skills.

• Excellent interpersonal skills and professional approach Skills desired.

• Exploratory tester with 2–3 years of experience in software testing.
• The candidate should be an expert in GUI and functional testing of web applications.
• Good communication is a must and should be capable of collaborating with cross functional teams.
• Should be self driven capable of handling responsibilities independently.
• Should have good knowledge of SQL and Jira
• Strong proficiency in Microsoft Excel is required for test analysis and reporting.
• Should be able to understand application architecture to effectively design and execute test scenarios.
• Experience with Playwright automation is an added advantage but not mandatory.

Responsibilities

• Develop, deploy, and maintain scalable products
• Participate in code reviews, and design discussions to ensure code quality and distribute knowledge
• Pair with team members for functional and non-functional requirements to write well-crafted, well-tested, readable, and maintainable code.
• Help to define roadmap and architecture based on technology and business needs
• Understand business requirements and work closely with the business to provide solutions

Eligibility

• Strong expertise in Backend Python Development with skills to create APIs, integrate the functions into UI, and store and retrieve data from a variety of databases.
• Strong experience with Django/Flask.
• Strong experience in writing unit tests.
• B.Tech/B.E (Preferred CSE)

Responsibilities

• Work on execution and scheduling of all tasks related to assigned projects' deliverable dates
• Optimize and debug existing codes to make them scalable and improve performance
• Design, development, and delivery of tested code and machine learning models into production environments
• Work effectively in teams, managing and leading teams
• Provide effective, constructive feedback to the delivery leader
• Manage client expectations and work with an agile mindset with machine learning and AI technology
• Design and prototype data-driven solutions

Eligibility

• Highly experienced in designing, building, and shipping scalable and production-quality machine learning algorithms in the field of Python applications
• Working knowledge and experience in NLP core components (NER, Entity Disambiguation, etc.)
• In-depth expertise in Data Munging and Storage (Experienced in SQL, NoSQL, MongoDB, Graph Databases)
• Expertise in writing scalable APIs for machine learning models
• Experience with maintaining code logs, task schedulers, and security
• Working knowledge of machine learning techniques, feed-forward, recurrent and convolutional neural networks, entropy models, supervised and unsupervised learning
• Experience with at least one of the following: Keras, Tensorflow, Caffe, or PyTorch

Company Details:

Company – PricewaterhouseCoopers (MNC Group)

Website     https://www.pwc.com/">https://www.pwc.com/

About PWC (PricewaterhouseCoopers) -PricewaterhouseCoopers is a multinational professional services network of firms, operating as partnerships under the PwC brand. PwC ranks as the second-largest professional services network in the world and is considered one of the Big Four accounting firms, along with Deloitte, EY and KPMG. PwC firms operate in 157 countries, 742 locations, with 276,000 people.

Job Role - Randstad Payroll (Client Inhouse)

Interview Process – Video Call Interview or Telephonic Interview

Salary – Best in Industry

Requirement -  Consultant and Experience Consultant

Qualification -  CA qualified/sCA semi-qualified 

Travelling - Yes

Roles and Responsibilities

1. Responsible for internal audit procedures and work programs for clients
2. Execute the assignment as per internal standards
3. Drafting of report as per internal standards
4. Ensuring compliance with Audit Standards & completing audits within timelines.
5. Good Comm. skills so as to communicate with clients independently on audit matters

Main Purpose of Job:

1. Responsible for Lead Generation and Client Conversion (Closing deals with Pharmacies and Doctors)

2. Working on Client Retention and Marketing Strategies (Onboarding patients by doing promotional activities)

3. Cold calling and Field sales activities.

Key Responsibilities / Accountabilities:

Key Activities - End Results

1. R&D for Lead Generation:

Will ensure lead generation and conversion as well.

2. Competitive Research Analysis:

Research will ensure less error rates and hence more efficiency.

3. Provide Weekly and Monthly reports:

Will show regular growth and advancements.

4. Identify potential market and test them extensively:

Opens new market ways and hence will help in increasing revenue.

5. Collecting and evaluating customer feedback:

Will show customer or client satisfaction.

6. Evaluating customer research, market conditions and competitor data:

Will provide more insights and hence increase productivity.

Competency Profile:

1. Experiences in delivering client focused solutions to customer needs.

2. Ability to work to budgets and deadlines.

3. Highly Energetic

4. Self-discipline & commitment

5. Innovative & Creative

6. Cost Consciousness

7. Efficient in Microsoft office (Excel & PowerPoint)

8. Good reasoning abilities. Sound judgment.

9. A creative approach to problem-solving skill

10. Tactful, mature, flexible.

11. Result oriented

12. Strategic Thinker

13. Build and Maintain strong, long lasting client relationship.

14. Strong verbal and written communication