Senior Solution EngineerJob Summary

We are looking for a hands-on Senior Solution Engineer with strong experience in AWS, Snowflake, software engineering, data engineering, and AI-enabled solutions.

The ideal candidate will design, build, deploy, and operate production-grade cloud-native data and AI solutions. The role requires strong engineering fundamentals, deep practical AWS and Snowflake experience, and the ability to take ownership of solutions from architecture through production support.

Experience

- 7+ years of skilled experience in Software Engineering, Solution Engineering, Data Engineering, or a related technical role.
- Proven experience delivering and operating production-grade enterprise solutions.
- Strong hands-on experience across the complete software development lifecycle.
- Experience building cloud services, data products, or AI-enabled solutions.

Key ResponsibilitiesSolution & Software Engineering

- Design, build, deploy, and operate production-grade software and data solutions end-to-end.
- Translate business requirements and ambiguous problems into scalable technical solutions.
- Develop clean, modular, reusable, maintainable, and testable code.
- Apply software engineering best practices including automated testing, CI/CD, observability, and secure development.
- Participate in architecture discussions, technical design reviews, code reviews, and pair programming.
- Perform debugging, performance tuning, root-cause analysis, and production issue resolution.

AWS Cloud Engineering

- Design and implement secure, scalable, and reliable cloud-native solutions using AWS.
- Hands-on experience with AWS services covering:
- Compute
- Storage
- Networking
- IAM and Security
- Serverless
- Orchestration
- Monitoring and Observability
- Event-driven architectures
- Build cloud-native integrations and automation using appropriate AWS services.
- Apply cloud security, governance, reliability, and cost optimization practices.

Snowflake & Data Engineering

- Design and implement scalable data pipelines and data products using AWS and Snowflake.
- Work with structured, semi-structured, and unstructured data.
- Design, model, curate, and optimize Snowflake datasets, schemas, and data structures.
- Perform SQL performance tuning and data pipeline optimization.




- Implement Snowflake access controls, data sharing, governance, and security.
- Ensure data quality, consistency, usability, performance, and cost efficiency.
- Support analytics, reporting, and AI/ML use cases.

AI & Generative AI

- Design and integrate AI-enabled capabilities into enterprise solutions.
- Experience with Amazon Bedrock and other AWS AI services is preferred.
- Familiarity with:
- Generative AI
- Agent-based AI architectures
- Retrieval-Augmented Generation (RAG)
- Model evaluation
- AI guardrails
- Responsible AI practices
- Work with data and cloud services to support modern AI use cases.

AI-Assisted Engineering

- Use AI-assisted engineering tools such as GitHub Copilot, Claude, Cursor, or similar tools in day-to-day development.
- Use AI tools for coding, refactoring, testing, debugging, documentation, and solution exploration.
- Validate AI-generated output using strong engineering judgement and quality standards.
- Familiarity with harness engineering or similar AI-assisted development practices is preferred.
- Understand prompt structuring, evaluation loops, reusable workflows, automated checks, and feedback mechanisms.

DevOps & Production Operations

- Follow Git-based development and CI/CD practices.
- Apply DevOps and infrastructure-as-code concepts.
- Own deployment, release, monitoring, and production operations.
- Troubleshoot production issues and perform RCA and performance optimization.
- Build appropriate observability and operational controls into solutions.
- Reuse proven engineering patterns and contribute to engineering standards.

Required Skills

- AWS – Deep hands-on experience
- Snowflake – Deep hands-on experience
- Python and/or Java – Strong programming skills
- Software Architecture & Solution Design
- Data Engineering & Data Pipelines
- SQL and Snowflake Performance Optimization
- REST APIs and Cloud Integrations




- Cloud-Native Development
- CI/CD
- Git
- Automated Testing
- DevOps
- Production Support
- Monitoring & Observability
- Infrastructure-as-Code concepts
- Cloud Security & IAM
- Data Governance

Preferred Skills

- Amazon Bedrock
- Generative AI / GenAI
- Agent-based AI solutions
- Retrieval-Augmented Generation (RAG)
- AI model evaluation and guardrails
- AI-assisted development
- GitHub Copilot / Claude / Cursor
- Harness Engineering
- AWS Certified Solutions Architect – Associate
- AWS Certified Data Engineer – Associate
- AWS Certified Machine Learning Engineer – Associate
- SnowPro® Core or advanced Snowflake certifications
- Financial Services / Banking / Financial Markets experience

Qualifications

- Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence / Machine Learning, or a related technical discipline.
- 7+ years of hands-on professional experience in software, solution, or data engineering.
- Proven ability to build and operate production-grade enterprise systems.
- Strong understanding of the Software Development Life Cycle (SDLC).
- Ability to translate ambiguous business problems into clear technical scopes and delivery plans.
- Strong analytical, problem-solving, and communication skills.
- Experience working with sensitive and confidential data.
- Ability to collaborate with business, technology, security, governance, risk, and other cross-functional teams.

Financial Services Experience

Experience in the financial industry is preferred, particularly exposure to:

- Financial markets
- Sensitive financial data
- Regulatory expectations
- Enterprise risk controls
- Data governance and security

Ideal Candidate

The ideal candidate is a hands-on Senior Solution Engineer who can independently own solutions from problem definition and architecture through development, deployment, monitoring, and production support.

The candidate should combine strong software engineering fundamentals with deep practical expertise in AWS and Snowflake, along with experience in modern data platforms, cloud-native architecture, and AI-enabled solutions.

Pay: Up to ₹1,680,000.00 per year

Work Location: Hybrid remote in Mumbai, Maharashtra

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