MIS Executive - Vile Parle - WFO

ey Responsibilities

✅ Architect, develop, and deploy AI-powered enterprise applications and intelligent automation solutions.

✅ Translate business requirements into scalable, secure, and production-ready AI systems.

✅ Build and integrate AI/ML capabilities into enterprise platforms and digital products.

✅ Design cloud-native applications leveraging AWS, Azure, or Google Cloud Platform (GCP).

✅ Develop APIs, microservices, distributed systems, and modern integration frameworks.

✅ Implement DevOps best practices, CI/CD automation, and engineering lifecycle processes.

✅ Utilize AI-assisted development tools to improve productivity and accelerate delivery.

✅ Ensure compliance with security standards, governance frameworks, and data privacy requirements.

✅ Collaborate with cross-functional teams, product stakeholders, and business leaders to deliver innovative solutions.

Required Skills

🔹 5+ years of experience in Software Engineering, Solution Architecture, or Enterprise Application Development.

🔹 Strong programming expertise in *Python, Java, TypeScript, or Go*.

🔹 Hands-on experience integrating AI/ML solutions into enterprise applications.

🔹 Experience with cloud platforms such as *AWS, Azure, or GCP*.

🔹 Strong understanding of *APIs, Microservices, Distributed Systems, and Containerization*.

🔹 Experience with *Agile methodologies, DevOps practices, and CI/CD pipelines*.

🔹 Knowledge of secure software development and enterprise governance standards.

🔹 Excellent problem-solving, communication, and stakeholder management skills.

Good to Have

⭐ Experience with *Machine Learning, Generative AI, Intelligent Automation, or LLM-based solutions*.

⭐ Knowledge of *MLOps, Prompt Engineering, Model Monitoring, AI Validation, and LLM Integration*.

⭐ Experience in *Banking, FinTech, Payments, or other regulated industries*.

⭐ Advanced degree in Computer Science, Artificial Intelligence, Engineering, or related fields.

⭐ Certifications such as *AWS/Azure/GCP Solutions Architect, TOGAF, CKA, or Lean Six Sigma*.

⭐ Experience leading engineering modernization, transformation, or automation initiatives.

⭐ Contributions to open-source projects and a passion for emerging technologies.

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.

We are looking for a skilled BI Engineer to join our team. The ideal candidate will have expertise in MicroStrategy, SQL, Reporting and Data Modeling along with experience in building insightful dashboards.

Key Responsibilities:

●Design, develop, and deploy MicroStrategy dashboards, reports, and visualizations.

●Write complex SQL queries to extract, manipulate, and analyse data from various sources.

●Develop and optimize data warehouse solutions for efficient data storage and retrieval.

●Collaborate with cross-functional teams to understand business requirements and deliver data solutions.

●Maintain and support MicroStrategy objects (attributes, facts, filters, prompts)

●Ensure data accuracy, consistency, and performance across reports and dashboards.

●Automate reporting processes and improve data visualization techniques.

●Troubleshoot data issues and optimize queries for better performance.

●Collaborate with business teams to understand reporting needs and translate them into visual insights.

●Work closely with business analysts, data engineers, and stakeholders to gather requirements and ensure solutions meet business needs.

Required Skills & Qualifications:

●5+ years of experience in BI engineering or data analytics.

●Strong expertise in MicroStrategy for dashboard, Data Modeling and report development.

●Knowledge of MicroStrategy architecture, Development and administration tools.

●Strong understanding of data modelling

●Perform data modeling and ETL validation to ensure accuracy of reports.

●Proficiency in SQL for querying and data manipulation.

●Experience working with data warehousing concepts and technologies (Redshift, Snowflake, BigQuery, etc.).

●Ability to process large datasets and optimize queries for performance.

●Strong analytical and problem-solving skills.

Preferred Qualifications:

MicroStrategy certification will be considered an added advantage.

Familiarity with the Tableau tool

                                               Sr. Data Engineer

Company Profile:

Bigfoot Retail Solutions [Shiprocket] is a logistics platform which connects Indian eCommerce SMBs with logistics players to enable end to end solutions.

Our innovative data backed platform drives logistics efficiency, helps reduce cost, increases sales throughput by reducing RTO and improves post order customer engagement and experience.

Our vision is to power all logistics for the direct commerce market in India

including first mile, linehaul, last mile, warehousing, cross border and O2O.

Position: Sr.Data Engineer

Team : Business Intelligence

Location: New Delhi

Job Description:

We are looking for a savvy Data Engineer to join our growing team of analytics experts. The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.

Key Responsibilities:

• Create and maintain optimal data pipeline architecture.
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Keep our data separated and secure across national boundaries through multiple data centres and AWS regions.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.

Qualifications for Data Engineer

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• A successful history of manipulating, processing and extracting value from large disconnected datasets.
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
• Strong project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment.
• We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
• Experience with AWS cloud services: EC2, EMR, RDS, Redshift
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.

What you need to have:

Profile Description:

The job holder will manage the day-to-day planning and operations of your team. This includes making sure that each of your Teammates delivers on their Service Level Agreement (SLA) and achieves their Key Performance Indicators (KPIs). As a Team Leader, you are in charge of managing the team and making sure everyone adheres to their schedules. You must be organized and be able to handle responsibility.

Key Responsibilities:

Project / Process:

1. Drive team to achieve process SLAs / metrics – productivity and quality targets within the established timelines.
2. Ensure individual SLAs are met on processing transactions (if applicable).
3. Ensure process guidelines are followed and met as documented.
4. Review process audit findings and take corrective action to prevent negative results.
5. Conduct Quality checks & periodical review of process adherence.
6. Maintain operations rigor around daily huddles, knowledge management Cross training etc.
7. Provide updates and submit reports related to own area of work.

Team Managements:

1. Provide work direction and guidance to team members:
2. ensure accuracy of the work of team members, their ability to operate under deadlines and to work on multiple tasks
3. Allocate work and tasks to the team.
4. Conduct team building activities to enhance motivation.
5. Conduct knowledge transfer sessions for new joiners in the team.
6. Identify training needs of team members and provide coaching support to them.
7. Report to the manager on performance, status and any escalations.
8. Manage attrition and absenteeism.
9. Developing and implementing a timeline to achieve targets.
10. Contributing to the growth of the company through a successful team.
11. Creating a pleasant working environment that inspires the team.

Designation - Enterprise Account Manager
from IT Software Company only. Emailing company background will be added 

advantage. 

Job description 

The Enterprise Account Manager (EAM) sells IceWarp collaboration solution direct to the company’s most 

strategic, complex Key accounts. EAM will have significant experience of selling complex software 

solutions to large enterprise accounts. Typically manages up to 15 qualified large Enterprise accounts. 

Primary Duties / Responsibilities 

1. Establish relationships and engage at executive levels within assigned accounts to identify and 

sell IceWarp products and services direct to the company’s most strategic, complex named 

accounts. 

2. Strong customer interaction at the Sr. Management level with support on forming a relationship 

with C level contacts within these accounts. 

3. Build up strategic contacts at CIO, managing director and executive level 

4. Carry a revenue quota to meet or exceed sales targets and demonstrate continuous progress 

towards achieving account strategies. 

5. Identify, develop, execute, and maintain account strategies to drive adoption of IceWarp product 

and services revenue within assigned enterprise accounts who are key, strategic and may have 

complex requirements. 

6. Establish and maintain close relationships with internal Presales, support, Marketing & 

Management team to access and leverage from appropriate internal resources. 

7. Provide regular and efficient updates on assigned accounts to sales management. 

8. Ensure accurate and timely forecasts in CRM. 

Knowledge, skills, abilities 

1. Demonstrated track record of establishing strategic executive level relationships to position and 

sell software and services to listed companies. 

2. Individual with 5-10 years’ experience of solutions sales with minimum 3 years’ experience in 

establishing strategic executive level relationships with Global 1000 enterprise customers. 

3. Proven ability to develop and maintain strong working relationships with internal marketing, 

technology, implementation, and product development teams. 

4. Strong consultative selling ability – critical questioning, listening, analytical, negotiation, 

communication, and presentation. 

5. Demonstrated ability to develop and articulate compelling qualitative and quantitative business 

cases for IT solutions. 

6. Proven ability to manage long, complex sales cycles from beginning to end and ability to close 

large complex deals with enterprise accounts. 

7. Excellent written and verbal communication skills including the ability to effectively present to both 

technical and executive audiences.