11+ Business Writing Jobs in Pune | Business Writing Job openings in Pune

MUST-HAVES:

• LLM, AI, Prompt Engineering LLM Integration & Prompt Engineering
• Context & Knowledge Base Design.
• Context & Knowledge Base Design.
• Experience running LLM evals

NOTICE PERIOD: Immediate – 30 Days

SKILLS: LLM, AI, PROMPT ENGINEERING

NICE TO HAVES:

Data Literacy & Modelling Awareness Familiarity with Databricks, AWS, and ChatGPT Environments

ROLE PROFICIENCY:

Role Scope / Deliverables:

• Scope of Role Serve as the link between business intelligence, data engineering, and AI application teams, ensuring the Large Language Model (LLM) interacts effectively with the modeled dataset.
• Define and curate the context and knowledge base that enables GPT to provide accurate, relevant, and compliant business insights.
• Collaborate with Data Analysts and System SMEs to identify, structure, and tag data elements that feed the LLM environment.
• Design, test, and refine prompt strategies and context frameworks that align GPT outputs with business objectives.
• Conduct evaluation and performance testing (evals) to validate LLM responses for accuracy, completeness, and relevance.
• Partner with IT and governance stakeholders to ensure secure, ethical, and controlled AI behavior within enterprise boundaries.

KEY DELIVERABLES:

• LLM Interaction Design Framework: Documentation of how GPT connects to the modeled dataset, including context injection, prompt templates, and retrieval logic.
• Knowledge Base Configuration: Curated and structured domain knowledge to enable precise and useful GPT responses (e.g., commercial definitions, data context, business rules).
• Evaluation Scripts & Test Results: Defined eval sets, scoring criteria, and output analysis to measure GPT accuracy and quality over time.
• Prompt Library & Usage Guidelines: Standardized prompts and design patterns to ensure consistent business interactions and outcomes.
• AI Performance Dashboard / Reporting: Visualizations or reports summarizing GPT response quality, usage trends, and continuous improvement metrics.
• Governance & Compliance Documentation: Inputs to data security, bias prevention, and responsible AI practices in collaboration with IT and compliance teams.

KEY SKILLS:

Technical & Analytical Skills:

• LLM Integration & Prompt Engineering – Understanding of how GPT models interact with structured and unstructured data to generate business-relevant insights.
• Context & Knowledge Base Design – Skilled in curating, structuring, and managing contextual data to optimize GPT accuracy and reliability.
• Evaluation & Testing Methods – Experience running LLM evals, defining scoring criteria, and assessing model quality across use cases.
• Data Literacy & Modeling Awareness – Familiar with relational and analytical data models to ensure alignment between data structures and AI responses.
• Familiarity with Databricks, AWS, and ChatGPT Environments – Capable of working in cloud-based analytics and AI environments for development, testing, and deployment.
• Scripting & Query Skills (e.g., SQL, Python) – Ability to extract, transform, and validate data for model training and evaluation workflows.
• Business & Collaboration Skills Cross-Functional Collaboration – Works effectively with business, data, and IT teams to align GPT capabilities with business objectives.
• Analytical Thinking & Problem Solving – Evaluates LLM outputs critically, identifies improvement opportunities, and translates findings into actionable refinements.
• Commercial Context Awareness – Understands how sales and marketing intelligence data should be represented and leveraged by GPT.
• Governance & Responsible AI Mindset – Applies enterprise AI standards for data security, privacy, and ethical use.
• Communication & Documentation – Clearly articulates AI logic, context structures, and testing results for both technical and non-technical audiences.

SENIOR DATA ENGINEER:

ROLE SUMMARY:

Own the design and delivery of petabyte-scale data platforms and pipelines across AWS and modern Lakehouse stacks. You’ll architect, code, test, optimize, and operate ingestion, transformation, storage, and serving layers. This role requires autonomy, strong engineering judgment, and partnership with project managers, infrastructure teams, testers, and customer architects to land secure, cost-efficient, and high-performing solutions.

RESPONSIBILITIES:

• Architecture and design: Create HLD/LLD/SAD, source–target mappings, data contracts, and optimal designs aligned to requirements.
• Pipeline development: Build and test robust ETL/ELT for batch, micro-batch, and streaming across RDBMS, flat files, APIs, and event sources.
• Performance and cost tuning: Profile and optimize jobs, right-size infrastructure, and model license/compute/storage costs.
• Data modeling and storage: Design schemas and SCD strategies; manage relational, NoSQL, data lakes, Delta Lakes, and Lakehouse tables.
• DevOps and release: Establish coding standards, templates, CI/CD, configuration management, and monitored release processes.
• Quality and reliability: Define DQ rules and lineage; implement SLA tracking, failure detection, RCA, and proactive defect mitigation.
• Security and governance: Enforce IAM best practices, retention, audit/compliance; implement PII detection and masking.
• Orchestration: Schedule and govern pipelines with Airflow and serverless event-driven patterns.
• Stakeholder collaboration: Clarify requirements, present design options, conduct demos, and finalize architectures with customer teams.
• Leadership: Mentor engineers, set FAST goals, drive upskilling and certifications, and support module delivery and sprint planning.

REQUIRED QUALIFICATIONS:

• Experience: 15+ years designing distributed systems at petabyte scale; 10+ years building data lakes and multi-source ingestion.
•  Cloud (AWS): IAM, VPC, EC2, EKS/ECS, S3, RDS, DMS, Lambda, CloudWatch, CloudFormation, CloudTrail.
• Programming: Python (preferred), PySpark, SQL for analytics, window functions, and performance tuning.
• ETL tools: AWS Glue, Informatica, Databricks, GCP DataProc; orchestration with Airflow.
• Lakehouse/warehousing: Snowflake, BigQuery, Delta Lake/Lakehouse; schema design, partitioning, clustering, performance optimization.
• DevOps/IaC: Terraform with 15+ years of practice; CI/CD (GitHub Actions, Jenkins) with 10+ years; config governance and release management.
• Serverless and events: Design event-driven distributed systems on AWS.
• NoSQL: 2–3 years with DocumentDB including data modeling and performance considerations.
• AI services: AWS Entity Resolution, AWS Comprehend; run custom LLMs on Amazon SageMaker; use LLMs for PII classification.

NICE-TO-HAVE QUALIFICATIONS:

• Data governance automation: 10+ years defining audit, compliance, retention standards and automating governance workflows.
• Table and file formats: Apache Parquet; Apache Iceberg as analytical table format.
• Advanced LLM workflows: RAG and agentic patterns over proprietary data; re-ranking with index/vector store results.
• Multi-cloud exposure: Azure ADF/ADLS, GCP Dataflow/DataProc; FinOps practices for cross-cloud cost control.

OUTCOMES AND MEASURES:

• Engineering excellence: Adherence to processes, standards, and SLAs; reduced defects and non-compliance; fewer recurring issues.
• Efficiency: Faster run times and lower resource consumption with documented cost models and performance baselines.
• Operational reliability: Faster detection, response, and resolution of failures; quick turnaround on production bugs; strong release success.
• Data quality and security: High DQ pass rates, robust lineage, minimal security incidents, and audit readiness.
• Team and customer impact: On-time milestones, clear communication, effective demos, improved satisfaction, and completed certifications/training.

LOCATION AND SCHEDULE:

●      Location: Outside US (OUS).

●      Schedule: Minimum 6 hours of overlap with US time zones.

Job Description:

· Proficient In Python.

· Good knowledge of Stress/Load Testing and Performance Testing.

· Knowledge in Linux.

Key Skills Required:

·         You will be part of the DevOps engineering team, configuring project environments, troubleshooting integration issues in different systems also be involved in building new features for next generation of cloud recovery services and managed services. 

·         You will directly guide the technical strategy for our clients and build out a new capability within the company for DevOps to improve our business relevance for customers. 

·         You will be coordinating with Cloud and Data team for their requirements and verify the configurations required for each production server and come with Scalable solutions.

·         You will be responsible to review infrastructure and configuration of micro services and packaging and deployment of application

To be the right fit, you'll need:

·         Expert in Cloud Services like AWS.

·         Experience in Terraform Scripting.

·         Experience in container technology like Docker and orchestration like Kubernetes.

·         Good knowledge of frameworks such as Jenkins, CI/CD pipeline, Bamboo Etc.

·         Experience with various version control system like GIT, build tools (Mavan, ANT, Gradle ) and cloud automation tools (Chef, Puppet, Ansible)

1.   In-Depth knowledge and experience with C# .NET Core are must.

2.   Experience in working with API Gateways, REST, SOAP, OAuth, SAML.

3.   Experience inworking with Kafka based environment.

4.   Microservices and Event driven Architecture (with a focus on cloud).

5.   Experience and understanding of OOPS and SOLID design principals.

6.   Well verse with Design Patterns.

7.   Familiarity with Azure and AWS offerings.

8.   Understanding of Relational and NoSQL databases SQL Server, Azure SQL, MongoDB, Elastic.

9.   Familiarity with the .NET framework

10. Familiar with various design and architectural patterns

11. Knowledge of concurrency patterns in C#

12. A willingness to get trained and work on cutting edge technologies like React, Node etc.

13. Understanding fundamental design principles behind a scalable application

14. Implementing automated testing platforms and unit tests

15. Proficient understanding of code versioning tools Git

Familiarity with CICD tools, JIRA, Azure devops etc

• Solve complex performance problems and architectural challenges
• Troubleshoot, test and maintain the core product software and databases to ensure strong optimization and functionality.
• Help team in technical challenges
• Code review and deployment
• Technical documentations
• Thorough understanding of React.js and its core principles.
• Familiarity with Restful APIs.
• Build efficient, testable, and reusable PHP modules.
• Should be able to understand the requirements & Develop web application.
• Ability to work on multiple projects at the same time and complete tasks in a timely manner.

“Re-imaging credit and payments from First Principles”

Payments is an interesting engineering challenge in itself with requirements of low latency, transactional guarantees, security, and high scalability. When we add credit and engagement into the mix, the challenge becomes even more interesting with underwriting and recommendation algorithms working on large data sets. We have eliminated the current call center, sales agent, and SMS-based processes with a mobile app that puts the customers in complete control. To stay agile, the entire stack is built on the cloud with modern technologies. 

OneCard (Best credit card app) : http://www.getonecard.app/">www.getonecard.app

OneScore (Over 10 million downloads): http://www.onescore.app/">www.onescore.app

What you will do:

• Execute new ways of attracting and hiring tech and product talent - PAN India across various technologies.
• Manage complete recruitment life cycle (Source > Screen > Interview > Hire)
• Conduct interview assessments combining various methods including technical assessments.
• Building a healthy talent pipeline across the tech/ product domain.
• Deliver exceptional candidate experience throughout the process.
• Collaborate with the HR team, delivering on key internal SLAs.
• Ability to conduct market intelligence in sourcing candidates, mapping, negotiating offers and decision-making.
• Manage vendor relationships.

Who you should be?

• Passionate about technology, hiring and networking with people.
• Minimum 3 to 5 years of Technical recruitment experience (preferably with Product/ Fintech Companies/ startups).
• Comfortable working with a fast-paced startup environment.
• Skilled with G-Suite applications, preferably ATS experience.
• Preferably someone with a technical education background.
• Strong communicator and go-getter.

Work Location: Aundh, Pune office (the role is on-site with WFH flexibility owing to environment and business drivers)

1. GCP Cloud experience mandatory
2. CICD - Azure DevOps
3. IaC tools – Terraform
4. Experience with IAM / Access Management within cloud
5. Networking / Firewalls
6. Kubernetes / Helm / Istio