11+ SFTP Jobs in Mumbai | SFTP Job openings in Mumbai

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.

Role & Responsibilities

• Own end-to-end data architecture across Medallion layers (Bronze/Silver/Gold) on AWS
• Design atomic star schema data models (fact and dimension tables) across multiple business domains
• Define and implement aggregation and KPI layers aligned to business reporting requirements
• Establish data modelling standards, naming conventions, and design patterns across teams
• Ensure alignment with enterprise data strategy and roadmap
• Translate business processes into scalable and reusable data models
• Write and review SQL, Python, and Spark code for pipelines and transformations
• Build and validate data models in Snowflake or Databricks
• Deliver pipelines using AWS services (S3, Glue, Athena)
• Perform data reconciliation and validation across layers (source → curated → BI)
• Ensure data quality, consistency, and integrity across the pipeline
• Own end-to-end SDLC (requirements → design → build → test → release → operate)
• Lead and unblock data engineers and analysts on day-to-day delivery
• Identify blockers, dependencies, and risks early, and propose solutions
• Align delivery with programme roadmap and milestones
• Track execution using Jira and maintain documentation in Confluence
• Gather and validate requirements across multiple business domains
• Translate business requirements into technical designs and data models
• Communicate architecture decisions clearly to non-technical stakeholders
• Drive cross-team alignment to ensure consistent, reliable, and trusted outputs

Ideal Candidate

• Strong Data Architect Profile (AWS / Medallion Architecture / Analytics Transformation)
• Mandatory (Experience 1) – Must have 8+ years of experience in Data Engineering / Data Architecture with strong exposure to large-scale analytics transformation programmes
• Mandatory (Experience 2) – Strong hands-on experience designing and implementing Medallion Architecture (Bronze / Silver / Gold layers) on AWS-based data platforms
• Mandatory (Experience 3) – Strong hands-on experience with Snowflake or Databricks, including data modelling, performance optimization, transformation pipelines, and scalable data warehouse implementations
• Mandatory (Experience 4) – Must have strong expertise in advanced SQL including complex joins, CTEs, window functions, query optimization, and performance tuning
• Mandatory (Experience 5) – Must have Hands-on development experience with Python and Apache Spark/PySpark for large-scale data transformation and processing pipelines
• Mandatory (Experience 6) – Strong experience working with AWS data services including S3, Glue, Athena, and cloud-native analytics/data lake architectures
• Mandatory (Experience 7) – Strong experience in end-to-end ETL/ELT pipeline development including ingestion, transformation, reconciliation, validation, testing, deployment, and production support
• Mandatory (Experience 8) – Experience working across transaction-heavy enterprise domains such as Finance, Supply Chain, HR, Customer, or Operations datasets
• Mandatory (Note) – Only immediate joiners or candidates who can join within 15 days will be considered
• Preferred (Experience) – Experience working with ERP / enterprise systems such as SAP, Oracle, Salesforce, or similar enterprise platforms
• Preferred (Frameworks) – Familiarity with APQC, SCOR, or enterprise process modelling frameworks is an added advantage

Job Description

Sr Executive – Accounts Receivable

Location: Andheri, Mumbai

Key Responsibilities

Collections Strategy & Management

 Develop and implement strategies to ensure mely collec on against invoices and billing.

 Monitor outstanding receivables, iden fy overdue accounts, and implement follow-up

mechanisms.

Team Leadership and Stakeholder Coordination

 Lead, mentor, and manage the collections team for op mal performance.

 Collaborate with sales, opera ons, and finance teams to resolve disputes and ensure

smooth collec ons.

 Communicate with customers professionally to resolve billing discrepancies and ensure timely payments.

Process & Technology Optimization

 Streamline billing and collection processes for efficiency and accuracy.

 Leverage ERP or other finance systems for tracking invoices, payments, and aging reports.

 Introduce automation and reporting dashboards to improve tracking and decision-making.

Reporting & Analysis

 Prepare regular reports on receivables, collection efficiency, and overdue accounts.

 Provide insights to senior management for cash flow planning and strategic decisions.

 Maintain proper documentation for audits and internal controls.

Key Skills & Competencies

 Strong understanding of accounts receivable, billing, and collec ons processes.

 Good communication on and problem-solving skills for customer interaction on.

 Knowledge of ERP/finance so ware and repor ng tools.

Qualification & Experience

 Graduate / Postgraduate in Finance, Commerce, Bank and Insurance or related field.

 3 – 5 years of experience in accounts receivable/collections, preferably in financial services

or BFSI sector.

 Proven experience leading a collections team and optimizing billing processes.

_____________________________

NO ONLINE INTERVIEWS

INTERVIEW IS IN OFFICE

LOCATION: THANE WEST 400604

_____________________________

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• Familiarity with technical SEO and analytics skills.
• Proficiency in image editing using Canva Pro.
• Ability to write content in clear and concise English.

Local residency is a requirement for this position.

Office Locations and Timings:

• Address: Ambika Nagar, Wagle Estate, Thane West 400604.
• Hours: Monday to Saturday, 9:00 AM to 7:00 PM.

Please note: We will share the exact interview address and timings with shortlisted candidates.

The role of the Key Account Manager - Sales is to bring new clients to Excellent Publicity through online & offline reach out and the below-mentioned work is carried out:

• Building the pipeline: Build a list of potential clients, reach out to them, fix meetings, gather requirements, share plans and get business. While there is a team to assist, the primary responsibility of pipeline building lies with the Account Manager
• Fixing Meetings: Reach out to the advertisers through cold calls/emails from the pipeline and set up meetings.
• Gather requirement: Use the meetings to gather requirements. In case there is no immediate requirement, maintain a relationship with the potential advertisers for future requirement
• Addressing the client requirements: Work closely with the media managers to address the client queries
• Campaign execution: Execute and monitor the campaigns. Remain the single point of contact for the advertiser in Excellent Publicity
• Maintain PR: Keep putting up efforts to increase business from existing clients.
•  

Other important skills and traits required to succeed in this role and Excellent Publicity, in general:

1. Good at identifying potential SMEs and Startups who can advertise

2. Ability to research and find relevant contacts in these organizations

3. Ability to understand client requirement and pitch relevant solution

4. Strong communication skills

5. Reliable and can work independently with minimum supervision

• Key Technical Skills: Deep experience on Performance Engineering with understanding of Java/J2EE technologies.
• Experienced in defining and realizing end-to-end Technical Architecture for large scale real- time enterprise systems. Ability to identify and define non-functional requirements and design systems to meet the same. 
• Ability to review existing Architectures and identify Risks, Trade-offs, and share recommendations for addressing the identified issues.
• Demonstrate strong understanding of cloud architecture considerations when scaling and tuning application deployments. Must have hands on experience working on any of the Cloud deployments on AWS or Azure. 
• Good experience on leveraging APM tools to provide deep dive analysis on performance problems. Deep understanding of the dashboards which can be built for CIO level interactions. Must have relevant experience on APM tools like Dynatrace or AppDynamics. 
• Experience in performance optimization of J2EE systems on any of different types of application servers - WebLogic, WebSphere, JBoss etc. Deep expertise in any one of the application servers is a must.
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• Experience in Big Data Analytics like - Apache Kafka, Apache Storm, Apache Hadoop, Apache Spark.
• Good skills in RDBMS like: Oracle, MS-SQL, MySQL, Cassandra, and Mongo DB 
• Exposure to Agile methodologies & Continuous Integration Tools 
• Entrepreneur / Intrapreneur (someone who has built technology teams ground-up, built new solutions from scratch) 
• Very sound understanding of technology and have a consultative approach. 
• Sound understanding of complex enterprise IT environment and issues faced by CIOs in the digital era. 
• Excellent Pre-sales experience and have played a key role in winning business along with the sales team. 
• Excellent communication, interpersonal, liaison and problem-solving skills with the ability to work in a multi-cultural environment 
• Good negotiation skills
• Go getter and results oriented 
• High energy level with ability to work well under pressure 
• Good relationship building skills. Someone who enjoys CIOs trust and has an ability to develop relationships at all levels (technology teams) of the customer organization.