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Rubiscape Private Limited

Prompt Engineering Specialist

Posted 10 Hours Ago
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In-Office
Pune, Maharashtra, IND
Mid level
In-Office
Pune, Maharashtra, IND
Mid level
Design, test, and refine prompt systems for production LLM agents supporting code generation, specification parsing, code review, documentation, and enterprise reasoning. Build versioned prompt libraries and evaluation frameworks, measure performance, investigate hallucinations and other failure modes, and collaborate with engineering teams to integrate reliable prompts into AI workflows. The role also requires documenting prompt decisions and staying current with techniques such as RAG, structured outputs, chain-of-thought, and tool use.
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About the Role

Rubiscape is building the Decision Intelligence Platform that India’s enterprises will run on for the next decade — and prompt engineering is the craft layer that makes our AI-first development workflows reliable at scale. As a Prompt Engineering Specialist, you will design, test, and iterate on the prompt systems that power Rubiscape’s internal LLM agents: from code generation and spec parsing to enterprise domain reasoning across BFSI, manufacturing, and healthcare verticals. You will work with real production LLMs, real enterprise complexity, and real performance constraints — building prompt libraries and evaluation frameworks that directly accelerate how Rubiscape ships software and how our platform surfaces AI insights to customers.

 

Key Responsibilities

·         Design, write, and iteratively refine prompt templates for internal LLM agents covering code generation, spec interpretation, code review, documentation, and enterprise domain reasoning tasks.

·         Build and maintain a structured prompt library: versioned, tested, and annotated prompts organised by task type, model target, and domain context (BFSI, manufacturing, healthcare, etc.).

·         Develop prompt evaluation frameworks: define success metrics, construct test sets, run A/B comparisons, and document prompt performance regressions and improvements.

·         Collaborate with Spec Engineering and AI Toolchain teams to ensure prompts are correctly parameterised by upstream specs and that outputs meet downstream code quality standards.

·         Investigate and mitigate failure modes in LLM outputs: hallucination, instruction drift, context loss, and domain-specific reasoning errors relevant to enterprise data and analytics workflows.

·         Stay current with advances in prompt engineering techniques (chain-of-thought, retrieval-augmented generation, structured output forcing, tool use) and adapt internal practices accordingly.

·         Document prompt design decisions, rationale, and empirical results in a shared knowledge base accessible to the entire engineering organisation.

Nice to Have

·         Experience with retrieval-augmented generation (RAG) architectures and vector databases (Pinecone, Weaviate, pgvector) in enterprise contexts.

·         Familiarity with the data engineering, BI, or analytics domain — ability to write prompts that reason correctly about SQL, data pipelines, ML model outputs, or business KPIs.

·         Prior work on multi-agent LLM systems where prompt design affects agent-to-agent communication and task decomposition.

·         Contributions to open-source prompt engineering toolkits, evaluation frameworks, or published benchmarks.

 

 

 

About Rubiscape

Rubiscape is India’s leading Decision Intelligence Platform, unifying data engineering, BI, machine learning, and agentic AI in a single governed platform. Built in Pune and trusted by Fortune 500 enterprises across BFSI, manufacturing, healthcare, and government. 8 international innovation patents. 10 Industry-Academia Labs & COEs. From BI to AI — One Platform. Every Decision.



RequirementsRequirements

·         3+ years of hands-on experience in prompt engineering, NLP engineering, or applied LLM development, with a demonstrable portfolio of production prompt systems.

·         Deep practical knowledge of major LLM APIs (OpenAI GPT-4/o series, Anthropic Claude, Google Gemini) including token economics, context window management, and structured output techniques.

·         Experience building prompt evaluation pipelines: automated test harnesses, LLM-as-judge patterns, or human evaluation workflows.

·         Strong Python skills for scripting prompt experiments, parsing LLM outputs, and integrating with LangChain, LlamaIndex, or equivalent orchestration frameworks.

·         Ability to reason clearly about enterprise domain complexity and encode that domain knowledge into reliable, reusable prompt structures.

·         B.E. / B.Tech in Computer Science, AI/ML, or Linguistics; or equivalent practical experience with a strong portfolio.



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