Prompt Engineering

Acura Solutions; Mumbai; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Acura Solutions is seeking an LLM Ops Specialist to bridge the gap between creative prompt design and robust system orchestration. You will own the design, evaluation, and production operation of foundation model-based systems, building scalable, observable infrastructure.

Responsibilities include system architecture, prompt engineering, LLM operations, and CI/CD for AI deployments, with emphasis on observability metrics like TTFT, throughput, and drift, plus cost control and cross-team

Qualifications

• Experience building and operating foundation-model systems.
• Proficiency in Python and AI tooling.
• Experience with RAG pipelines and prompt architecture.

Responsibilities

• Design end-to-end AI systems that integrate multiple models and retrieval systems.
• Craft prompts and manage a Prompt Registry for versioning and A/B testing.
• Implement observability and cost controls for LLM-based deployments.
• Develop CI/CD pipelines and evaluation suites for regressions.
• Ensure integration of AI workflows with existing software systems.

Skills

Python

Prompt frameworks

RAG pipelines

Structured data integration

Job description

Role & responsibilities

prompt

Role Summary: We are seeking a versatile engineer to bridge the gap between creative prompt design and robust system orchestration. You will own the design, evaluation, and production operation of our foundation model-based systems. As an LLM Ops Specialist, you will be responsible for building the infrastructure that makes these systems scalable, optimized and observable.

Core Responsibilities

System Architecture & Orchestration

• Design end-to-end compound AI systems integrating multiple models, retrieval systems, and agentic workflows.

Prompt Engineering & Versioning

• Craft structured, few-shot, and chain-of-thought prompts to reduce hallucinations and ensure predictable outputs.
• Develop and manage a Prompt Registry to track versioning and A/B test results.

LLM Operations (LLM Ops)

• Observability: Instrument real-time monitoring for LLM-specific metrics, such as:
  • Time to First Token (TTFT)
  • Token throughput
  • Drift detection
• Cost Control: Implement semantic caching and intelligent model routing to reduce API spend.
• CI/CD for AI: Build evaluation suites and methodologies to test for regressions on every deployment.

Core Tech Skills

• Python Proficiency
• Hands-on with Programmatic Prompting Frameworks
• Experience with Retrieval-Augmented Generation (RAG) Pipelines
• Experience with Structured Data Control and Integrations into other Software Systems

Mandatory Soft Skills

• Excellent Written and Spoken Communication Skills, to the Degree of Clinical Precision
• Excellent Tech-to-Business Translations
• Analytical Thinking pertaining to Problem Decomposition and Adversarial Thinking
• Collaborative Agility - Must have ability and willingness for Cross-Team Functionality and Faster Feedback

Integration Loop

• Constant Experimentation Mindset and High Degree of Learning Agility