Meltplan

Construction

AISystemsQAEngineer

₹19–33L ~AI est. India
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“AI Systems QA Engineer at Meltplan. Skills: AI QA, LLM evaluation, System testing. Design evaluation frameworks. Develop evaluation frameworks”

What You'll Achieve.

Enhance accuracy; Enhance safety; Improve performance; Improve system reliability; Improve model behavior

Industry & Context.

Construction
Problems you'll solve

Analytical skills; Debugging skills; Problem-solving skills; Root cause analysis

What They're Looking For.

Must Have

Bachelor's degree in Computer Science, 5–8 years of experience in QA/testing, Experience in AI/LLM evaluation frameworks, Experience in system testing, Hands-on experience with automated testing, Experience working with Python, Experience with testing frameworks

Nice to Have

Experience in AI/ML or data-driven systems, Exposure to OpenAI Evals, Exposure to LangSmith, Exposure to DeepEval, Exposure to Promptfoo, Worked in construction, Startup experience, Experience with Generative AI, Experience with conversational AI products, Knowledge of CI/CD pipelines, Knowledge of automation workflows, Prior experience in performance testing, Prior experience monitoring distributed systems, Understanding of AI product lifecycle, Understanding of production deployment environments

What You'll Do.

Design evaluation frameworks

Develop evaluation frameworks

Execute evaluation frameworks

Perform end-to-end system testing

Perform regression testing

Perform performance testing

Validate model outputs

Build automated test pipelines

Build quality benchmarks

Collaborate with AI/ML engineers

Collaborate with product teams

Collaborate with platform engineers

Provide actionable feedback

Develop testing scenarios

Measure model performance

Monitor production performance

Improve evaluation metrics

Improve testing standards

Ensure compliance with responsible AI

Ensure compliance with quality assurance

How You'll Work.

Team & Collaboration

AI/ML engineers; Product teams; Platform engineers

Full Job Description

MeltPlan is building the “planning engine” for the $14 Tn construction industry, an AI system designed specifically to optimize decisions before construction begins. While design software optimizes use and aesthetics and construction software optimizes execution and control, MeltPlan is building the missing layer - software that optimizes decisions and tradeoffs upstream, before scope is locked, procurement begins, and change orders become inevitable. MeltPlan’s long-term goal is to help teams make construction “boring” by making planning more intense: surfacing constraints and tradeoffs early, aligning stakeholders before plans are frozen, and reducing the need for late-stage redlines, rework, and change orders. MeltPlan is founded by operators who have built at scale. Kanav previously co-founded Innovaccer, a $3Bn healthtech company focused on making US healthcare more affordable and accessible. He’s now applying that systems-level thinking to construction.He’s joined by Tanmaya Kala, former Project Executive at DPR Construction, who led large commercial, healthcare, and life sciences projects. We combine deep tech scale with real construction execution. What This Role Really is : We are seeking a detail-oriented and technically strong AI QA Engineer to ensure the quality, reliability, and performance of Large Language Model (LLM)-based systems. In this role, you will be responsible for designing and executing test strategies, validating model outputs, and building evaluation frameworks to enhance the accuracy, safety, and overall performance of AI-driven applications.We would particularly value candidates who have hands-on experience in developing evaluation frameworks (evals) for AI systems, along with strong expertise in comprehensive system testing and quality assurance practices.You are responsible for making MeltPlan work in the real world. What You'll Do: Design, develop, and execute evaluation frameworks (Evals) for Large Language Models (LLMs) and AI syst

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