Software Engineering Lead - Data Services
New
J
JobgetherB2B Sales Intelligence
Based in IndiaFull-TimeLead
SalaryCompetitive base compensation and meaningful equity participation.
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Job Details
- Experience
- 7–10 years of hands-on backend engineering experience
- Required Skills
- AWSPostgreSQLPythonSQLDynamoDBGCPSnowflakeFastAPINosql
Requirements
- 7–10 years of hands-on backend engineering experience.
- Experience leading engineers or engineering leads.
- At least 3 years of strong hands-on Python development.
- Expertise with FastAPI, Pydantic, and modern backend engineering practices.
- Proven experience building and operating large-scale production systems.
- Demonstrated experience shipping AI/LLM services, APIs, and agents into production.
- Strong experience with AI harness engineering, tool-calling frameworks, and agent runtimes.
- Solid data-modeling expertise across both SQL and NoSQL databases.
- Practical experience with agentic development environments such as Claude Code or Cursor.
- Experience with AWS or GCP (ECS/Fargate, Lambda, S3, RDS, DynamoDB).
- Familiarity with AI evaluation/observability tools like Braintrust, Inspect AI, Promptfoo, or OpenTelemetry.
- Experience with agent frameworks like LangGraph or Pydantic AI is advantageous.
Responsibilities
- Own the architecture, development, and operation of secure, scalable backend services and RESTful APIs using Python and FastAPI.
- Design robust data models, schemas, and integrity strategies across PostgreSQL, Snowflake, and DynamoDB.
- Build and evolve production AI/LLM services and agents with a focus on performance, observability, and reliability.
- Develop agent infrastructure including tool-calling frameworks, MCP server layers, and sandboxed execution.
- Establish AI evaluation frameworks including scorers, regression suites, model calibration, and drift detection.
- Lead two engineering pods through team leads, conducting code reviews and setting high engineering standards.
- Partner with cross-functional teams to translate product requirements into production-ready architectures.
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