Prompt Engineer

Position:
Prompt Engineer

Employment Type:

Full Time

Experience:

2–5 Years in Prompt Engineering, LLM Application Design, AI Engineering, or Applied NLP (B2B, SaaS, or Enterprise AI Environments)

Company Description

Scry AI is a research-led enterprise AI company that builds intelligent platforms for BFSI, insurance, logistics, and industrial enterprises to drive efficiency, insight, and compliance. Our product suite includes Auriga for conversational AI, Collatio for document intelligence, and Concentio for cognitive IoT and operational intelligence. These platforms help clients convert complex, fragmented data into actionable enterprise intelligence.

We are looking for a Prompt Engineer to design, test, and optimize prompts and interaction frameworks that power Scry AI’s enterprise AI platforms. This role is critical in ensuring consistent, accurate, safe, and explainable outputs across document intelligence, conversational AI, and decision-support use cases.

Role Overview

As a Prompt Engineer at Scry AI, you will be responsible for crafting high-quality prompts, system instructions, and evaluation frameworks for large language models embedded in production systems. You will work closely with product, engineering, data science, and domain experts to translate business workflows into reliable AI behaviors.

This role is ideal for someone who combines strong language intuition with a deep understanding of LLM behavior, enterprise risk constraints, and real-world production requirements.

Key Responsibilities

Prompt Design and Optimization

- Design and refine prompts, system instructions, and multi-step prompt chains for enterprise use cases
- Optimize prompts for accuracy, consistency, latency, and cost efficiency
- Handle edge cases, ambiguity, and adversarial inputs through structured prompting techniques

Evaluation, Testing, and Reliability

- Develop prompt evaluation frameworks, test suites, and success metrics
- Continuously test prompts against real-world data, drift scenarios, and model updates
- Analyze failures, hallucinations, and inconsistencies, and propose mitigation strategies

Enterprise AI Behavior and Guardrails

- Embed domain rules, policies, and constraints into prompt logic
- Collaborate on safety, compliance, and explainability guardrails for regulated environments
- Ensure outputs align with enterprise governance and auditability requirements

Cross-Functional Collaboration

- Work closely with product managers to understand workflows and user intent
- Partner with engineers and data scientists to integrate prompts into production pipelines
- Collaborate with domain experts to encode business logic and terminology into prompts

Documentation and Knowledge Sharing

- Document prompt logic, design rationale, and expected behaviors
- Create reusable prompt templates and best-practice libraries
- Support internal enablement by sharing learnings and prompt patterns

Required Qualifications and Skills

- 2+ years of hands-on experience working with large language models in production or near-production settings
- Strong understanding of prompt engineering techniques such as few-shot prompting, chain-of-thought control, role prompting, and tool calling
- Experience evaluating LLM outputs for accuracy, bias, and reliability
- Comfort working with APIs, JSON schemas, and structured outputs
- Ability to translate complex business workflows into clear, deterministic AI behaviors

Preferred Qualifications

- Experience working with enterprise AI platforms, RAG pipelines, or document intelligence systems
- Understanding of model limitations, drift, and evaluation strategies
- Background in NLP, linguistics, computer science, or applied AI
- Exposure to regulated domains such as BFSI, healthcare, or insurance

Our Ideal Candidate

- Thinks in systems, not just prompts
- Obsesses over reliability, consistency, and edge cases
- Balances creativity with structure and discipline
- Is curious about how humans and AI interact at scale
- Enjoys turning ambiguous requirements into precise, repeatable outcomes

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