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Akshitha Akula
Mid-Level Full-Stack Python Engineer specializing in cloud APIs and data/ML platforms
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About
Backend engineer at Goldman Sachs who deployed internal LLM-powered utilities to summarize operational logs/tickets, with a strong emphasis on data sensitivity and reliability. Built deterministic workflows with template-based prompts, confidence checks, and rule-based fallbacks, and used monitoring plus failure-rate metrics to tune performance; also has hands-on Temporal orchestration experience for resilient async backend jobs.
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Key Strengths
- Production LLM utility design with strong reliability safeguards (scoped inputs, template prompts, fallbacks)
- Pragmatic model selection focused on cost/quality tradeoffs and avoiding LLMs when rule-based logic suffices
- Operational rigor: logging/monitoring, retries/timeouts, and measuring failure rates and fallback triggers
- Workflow orchestration for reliable long-running async backend processes (Temporal)
- Effective collaboration with non-technical stakeholders via expectation-setting, iterative demos, and feedback-driven refinement
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