Senior Forward Deployed Engineer
Spaulding Ridge (company site, opens in a new tab)10+ yrsBengaluruOn-siteDirect career pageEst. 28–45 LPA
Posted 4h ago
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Job description
Structured overview of role & requirements
About This Role
- Own client-facing delivery of data and AI-enabled solutions, from workflow discovery and prototypes through production rollout, adoption and outcome measurement.
- Make and implement architecture decisions across Snowflake, data pipelines, APIs and applications; personally code and troubleshoot critical components, including LLM-enabled workflows where useful.
- Lead technical delivery and mentor engineers while managing estimates, risks and trade-offs; contribute to project scoping and reusable practice accelerators.
Minimum Requirements
- Work Experience Required: 10+ years of relevant consulting or industry experience, including hands-on software or data engineering and production delivery; bachelor’s degree or equivalent relevant education and professional experience.
- Strong hands-on Snowflake and SQL, including data modeling, ingestion, access controls, performance and cost optimization; production data pipelines and transformations using dbt or comparable tools.
- Strong Python, JavaScript or TypeScript skills and experience delivering applications across interface, API and data layers; secure REST integrations, Git, testing, CI/CD, deployment and production troubleshooting.
- Hands-on experience building and testing an LLM application or tool-using agent connected to business data or systems, including evaluation and controls; practical use of an AI-assisted development tool with generated output review and client-data protection.
Ideal Candidate Profile
- Has delivered Office of the CFO solutions, especially financial close and reconciliation, management reporting, FP&A, variance analysis or working-capital workflows; this domain experience is strongly preferred.
- Combines client discovery with pragmatic engineering: translates ambiguous workflows, business rules and approval needs into a useful first release, then iterates based on user feedback and measured results.
- Fits a manager-grade technical leadership role, remaining hands-on while guiding engineers and owning delivery across data, applications and production AI workflows.