Sales Intern

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-Sr. Engineer – Costing / Assistant Manager – Costing.

Working Days-6 Days (WFO)

Location-Pune (Chakan)

Job Description – Costing

Industry- Wiring Harness

Key Responsibilities

Costing Operations

• Ensure timely submission of quotations to customers.
• Handle copper amendments for all customers as required.
• Update prices in SAP as per the latest Purchase Order (PO).
• Ensure timely submission of supplementary invoices to all customers.
• Follow up with customers for pending POs.
• Take initiative in controlling and optimizing costs.

Strategic Planning

• Maintain strong relationships with clients to ensure smooth business operations, especially in costing-related matters

Client Servicing

• Manage customer service operations related to costing and ensure timely delivery.
• Resolve any costing-related issues efficiently.
• Deliver value-added costing presentations to customers.
• Monitor ongoing costing and manage price revisions/amendments as needed.

Skills & Job Requirements

• Strong leadership and interpersonal skills.
• Excellent communication and presentation abilities.
• Strategic thinking with a results-oriented mindset.
• Strong analytical and conceptual skills with attention to detail.
• Proactive approach with high energy levels.
• Good techno-commercial understanding.
• Strong capability in cost analysis.
• Understanding of customer and market dynamics.
• Creative and innovative thinking skills.
• Awareness of IATF and EMS standards.

Lead / Sr. Data Engineer (Architect & Engineering Owner)

The Role

We are seeking a Lead Data Engineer who operates at the intersection of high-scale engineering and enterprise architecture. In this role, you will "own" our healthcare data platform end-to-end. You aren't just building pipelines; you are designing the blueprint for how clinical, claims, and sales data flow through our ecosystem. You will bridge the gap between legacy systems (MSSQL/Oracle) and modern cloud warehouses (Snowflake/Redshift/Databricks), ensuring our data is governed, HIPAA-compliant, and optimized for advanced analytics.

What You’ll Do

1. Architecture & Strategic Leadership

• Design the Blueprint: Own the enterprise data architecture (Staging, Integration, Warehouse, and Semantic layers). Define the evolution from monolithic databases to scalable cloud-hosted analytics.
• Modeling Mastery: Lead the design of complex Dimensional Models (Star/Snowflake) and implement advanced Slowly Changing Dimension (SCD) strategies to track historical clinical events.
• Set the Standard: Establish coding, version control (GitHub), and CI/CD standards. Conduct design reviews and mentor a team of engineers to move from "task-takers" to "system-builders."

2. Advanced Data Engineering (Hands-on)

• Modern ELT/ETL: Build and orchestrate production-grade pipelines using Python, Airflow, and dbt. Manage automated ingestion via Fivetran or custom-built frameworks for APIs and EHRs.
• Multi-Engine Expertise: Operate seamlessly across PostgreSQL, MSSQL, and Oracle, while optimizing petabyte-scale cloud warehouses like Snowflake or Redshift.
• Performance Tuning: Own query optimization. You should be the expert at using EXPLAIN/ANALYZE, partitioning, and indexing to reduce compute costs and latency.
• Quality & Reconciliation: Design robust validation frameworks to ensure data integrity—essential for healthcare compliance and clinical trust.

3. Healthcare Interoperability & Governance

• Data Standards: Map diverse datasets (EHR, API, Flat Files) to HL7 FHIR resources and curated analytic layers.
• Privacy by Design: Embed HIPAA Security Rule safeguards (encryption, audit trails, and access controls) directly into the code and infrastructure.
• Interoperability: Handle complex semi-structured data (JSON/XML) from third-party partners and EMR systems.

What You’ll Bring

• Experience: 8–12+ years in Data Engineering/Architecture. You should have a track record of leading technical projects or mentoring teams.
• The "Hybrid" Stack: * Expert SQL/PL-SQL: Deep experience with performance tuning in relational environments (Oracle/MSSQL).
• Modern Tools: Practical experience with Snowflake/Redshift, dbt, and Airflow.
• Programming: High proficiency in Python (Pandas, PySpark) or Java/Scala for custom ETL routines.
• Architectural Depth: Clear understanding of SDLC, Agile (Scrum), and Data Modeling frameworks.
• Healthcare Domain: Exposure to pharmaceutical or clinical data (Life Sciences, EMR, or Claims) is highly preferred.
• Soft Skills: The ability to translate "clinical business needs" into "technical runbooks" and communicate effectively with stakeholders.

Nice to Have

• AI/ML Integration: Experience supporting Data Science teams with feature extraction and model deployment (SageMaker/Azure ML).
• Advanced Tooling: Familiarity with NoSQL (MongoDB), search engines (Elasticsearch), or niche ETL tools (Talend/Informatica) for migration purposes.
• Cloud Infrastructure: Hands-on experience with AWS Glue, Lambda, or Azure Data Factory.

Key Responsibilities:

·        Connect with clients and resolve their queries via calls, remote desk, and email support.

·        Resolve tickets generated by clients for technical requests and issues to ensure seamless operations.

·        Assist in designing and implementing successful software solutions.

·        Track user tickets and maintain resolution records.

·        Coordinate with the development team for feature enhancements and technical improvements.

Job Description:

We are seeking an experienced Cognos Developer with strong expertise in Cognos Analytics 11 (C11) to design, develop, and maintain interactive dashboards and reports. The ideal candidate will work closely with business stakeholders to translate requirements into scalable BI solutions, leveraging Cognos Framework Manager, Report Studio, and Dashboard capabilities.

Key Responsibilities:

• Develop and maintain reports and dashboards using Cognos C11.
• Work with stakeholders to gather and analyze reporting requirements.
• Design data models and metadata using Framework Manager.
• Optimize report performance and troubleshoot issues.
• Ensure data accuracy and report integrity.

Required Skills:

• 3+ years of experience with IBM Cognos (preferably C11).
• Proficient in creating dashboards, visualizations, and reports.
• Strong SQL and data analysis skills.
• Experience with Framework Manager and Data Modules.
• 
  

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Thirega@ vysystems dot com - WhatsApp - 91Five0033Five2Three

**Company Overview**

We are a VC-backed fintech startup developing an innovative online trading platform. As we scale, we're seeking a skilled Backend Engineer with expertise in Python to join our growing team and help build a robust, scalable infrastructure for our cutting-edge trading application.

We're based out of the UK and have our engineering team in India.

**Job Description**

We are looking for a backend developer who specialises in Python. Your role will focus on developing and maintaining the server-side logic, optimising performance, and ensuring seamless integration with the frontend. You’ll work closely with the engineering and product teams to deliver a high-quality, secure, and scalable platform.

**Responsibilities**

1. Develop and maintain server-side logic using Python

2. Design and implement APIs for seamless integration with frontend components

3. Optimise backend performance and scalability for high traffic and large data loads

4. Build and maintain databases, ensuring security, data integrity, and optimal performance

5. Collaborate with frontend engineers to ensure smooth integration between backend and frontend systems

6. Troubleshoot, debug, and optimise backend infrastructure

7. Implement data protection, security protocols, and authentication mechanisms (e.g., JWT)

8. Maintain and enhance real-time communication systems using WebSockets or similar protocols

**Required Skills**

1. Strong proficiency in Python and related technologies, knowledge of databases and SQL, and experience with web frameworks like Django or FastAPI

2. Strong analytical and troubleshooting skills, and the ability to solve problems

3. Good understanding of OOPs, task broking services, Queues, Redis

4. Familiarity with RESTful API design and integration

5. Strong understanding of database management (e.g., PostgreSQL, Redis) and caching strategies

6. Familiarity with modern authentication and authorization mechanisms (e.g., JWT, OAuth)

7. Proficiency in working with cloud hosting services (AWS, Google Cloud, etc.)

8. Experience with containerization and orchestration tools (Docker, Kubernetes)

9. Knowledge of real-time communication protocols (e.g., WebSockets, TCP, SSE)

10. Strong understanding of security best practices for server-side applications

11. Experience with version control (Git) and CI/CD pipelines

12. Minimum of 2-3.5 years of experience building scalable backend systems

**Perks**

1. Work From Anywhere Flexibility

2. Unlimited Leaves policy*

3. Competitive salary and unlimited growth opportunities

4. Insights on how HFT is done using cutting edge technology

If you’re passionate about building scalable, high-performance backend systems and want to be part of a cutting-edge fintech startup, we’d love to hear from you!

• Designing and building mobile applications for Apple’s iOS platform.
• Collaborating with the design team to define app features.
• Ensuring quality and performance of the application to specifications.
• Identifying potential problems and resolving application bottlenecks.
• Fixing application bugs before the final release.
• Publishing application on App Store.
• Maintaining the code and atomization of the application.
• Designing and implementing application updates