Overview The Prompt Engineer is a specialist in building, expanding, and managing AI Agents that power project44 s AIA Operations organisation. Acting as both an AI workflow architect and operational strategist, the Prompt Engineer plays a central role in designing, governing, and scaling the operational frameworks that underpin AIA Operations globally.

What you'll own

This role partners closely with global Product, Engineering, AI, and Operations leaders to shape AI Agents long-term performance trajectory, define engineering standards, and embed best practices that strengthen consistency and scalability across regions. The Prompt Engineer operates as an individual contributor - driving measurable operational improvement through deep domain expertise, disciplined experimentation, and cross-functional collaboration.

AI Workflow Development Prompt Engineering

- Design, build, and maintain AI agent workflows that automate carrier monitoring, performance tracking, exception management, and escalation processes.
- Build custom, customer-specific AI agent workflows tailored to individual carrier, lane, or account requirements, adapting core workflow patterns to unique operational needs.
- Write, test, iterate, and optimise prompts for large language models, ensuring accuracy, reliability, and operational efficiency.
- Run structured tests to evaluate prompt performance, comparing variants against defined criteria and documenting what works, what doesn t, and why.
- Track prompt versions and iterations, maintaining clear records of changes, evaluation outcomes, and the reasoning behind design decisions.
- Identify where LLM outputs fall short of operational requirements and systematically diagnose and resolve issues through prompt refinement.
- Work closely with engineers through the handover and deployment process, ensuring workflows are correctly implemented and behave as intended at go-live.
- Ramp up recent use cases post-launch - gradually expanding scope and coverage, surfacing edge cases as real-world volume increases, and refining prompts accordingly.
- Monitor agent performance on an ongoing basis, identifying drift, degradation, or failure modes and re-iterating on prompts to maintain accuracy and reliability over time.
- Maintain and support existing production workflows throughout their lifecycle, applying fixes, updates, and enhancements as customer needs, data sources, or underlying models evolve.
- Evaluate new AI tools and platforms,



providing structured recommendations on adoption and integration into existing team workflows.

Operational Governance

- Continuously increase AI Agent build velocity by escalating process pain points and driving improvements.
- Identify opportunities to expand automation coverage and proactively bring forward structured proposals for new AI capabilities.
- Support continuous improvement across the full AI Agent build lifecycle, including process optimisation and efficiency gains. Cross-Functional Collaboration

- Read and interpret Product Requirements Documents (PRDs), transforming them into clear AI agent requirements that define what the workflow needs to do, how success will be measured, and what constraints apply.

- Work with Product Managers throughout the full agent build lifecycle - from initial requirements through to go-live - ensuring the agent is built to expectations and flagging any gaps or ambiguities early.
- Work closely with engineers who build the connectors that deploy AI agents, ensuring clear handover of prompt designs and workflow logic, and collaborating through go-live to resolve any issues.

- Collaborate with external vendors to reduce friction and influence new feature releases.

Customer Collaboration

- Partner directly with customers to understand their operational goals and translate them into tailored AI agent workflows and clear success criteria.

- Work directly with customers post-launch to review agent performance, gather feedback, and drive iterative improvements that increase accuracy and value delivered.
- Serve as a subject-matter point of contact for customers on agent behaviour, troubleshooting, and enhancement requests, balancing customer needs with engineering feasibility.

Team Enablement

- Contribute to training resources, internal knowledge bases, and team documentation that raise the AI capability of the broader function.
- Champion a culture of disciplined experimentation, continuous learning, and rigorous quality standards across the team.

Experience

- 3-4+ years in transportation operations, logistics technology, carrier management,



or network operations; global or multi-region experience preferred.

- Hands-on experience working with AI tools, automation platforms, or workflow-based technologies in an operational context.
- Troubleshooting experience across EDI, API, data pipelines, system configuration, and workflow orchestration.

- Strong analytical skills - comfortable using data, monitoring dashboards, and structured observation to diagnose problems and measure outcomes.
- Demonstrated ability to work collaboratively across Product, Engineering, AI, and Operations stakeholders.

- Excellent written and verbal communication skills; able to read and interpret product requirements and translate them into clear, structured specifications for AI workflows. Prompt Engineering AI Skills

- A genuine curiosity about how LLMs work and a methodical approach to testing and refining prompts - patience and rigour matter more than prior formal training.
- Ability to write clear, structured prompts and instructions that direct AI behaviour accurately and consistently.

- Familiarity with core prompting techniques such as step-by-step instructions, examples within prompts (few-shot), and breaking complex tasks into stages.
- Comfort working in AI tools and platforms to build, test, and iterate on workflows without needing to write code.

- Ability to critically evaluate LLM outputs - spotting errors, inconsistencies, and failure modes - and translate observations into targeted prompt improvements.
- An understanding of LLM behaviour and limitations - including how models can hallucinate, misinterpret instructions, or produce inconsistent outputs - and how to design prompts that account for these tendencies.

Success Profile

- Scaled, productionised AI workflows that drive measurable improvements in automation coverage, accuracy, and operational efficiency.
- Accelerated resolution of complex, high-impact incidents through expert diagnostics and systemic remediation.

- Effective cross-regional governance and operational standardisation that enhances global team maturity.
- recognised expertise that strengthens organisational capability and advances AIA Operations AI transformation roadmap.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Prompt Engineer (Bengaluru)
🏢 Project44
📍 Bengaluru