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Cognicorvia Indeed
Senior Prompt Engineer
REMOTEPosted 4mo ago
ML EngineerMid LevelFull-time#python#llm#nlp#aws#azure
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About the Role
Role Description
This is a full-time hybrid role for a Senior Prompt Engineer based in Kochi, with the flexibility for some remote work. The Senior Prompt Engineer will be responsible for crafting and fine-tuning prompts for Generative AI models, collaborating with cross-functional teams to develop scalable AI-driven solutions. The candidate will perform in-depth research to optimize responses, evaluate AI model outputs, and iteratively refine prompt engineering strategies to align with business requirements. This position involves continuous learning, collaboration, and innovative problem-solving to ensure the effectiveness and accuracy of the AI models.
Role Summary
The Senior Prompt Engineer will design, optimize, and govern prompt strategies for large language model driven AI copilots used in financial advisory and wealth management workflows.
The role focuses on improving response accuracy, reasoning quality, safety, and user experience across Cognicor’s AI platforms.
The individual will collaborate with product, engineering, data, and UX teams to deliver production grade Generative AI solutions.
Immediate or short notice candidates are preferred due to urgent demand.
Key Responsibilities
Prompt Design, Development, and Optimization
- Design, test, and refine prompts for LLM based conversational and task automation systems.
- Apply zero shot, few shot, and chain of thought prompting techniques to improve reasoning and output quality.
- Break down complex business problems into logical sub tasks for iterative prompting and functional analysis.
- Build reusable prompt libraries, evaluation datasets, and governance standards.
- Continuously tune prompts using telemetry, feedback loops, and measurable performance metrics.
Iterative Testing and Quality Assurance
- Conduct systematic regression testing across multiple scenarios, edge cases, and workflows.
- Validate robustness, consistency, and reliability of AI responses before production release.
- Define evaluation benchmarks and automated prompt testing strategies.
Safety, Compliance, and Risk Controls
- Implement guardrails to reduce hallucinations, bias, unsafe outputs, and prompt injection risks.
- Ensure explainability, auditability, and regulatory alignment for AI responses in financial services environments.
- Partner with security and compliance teams to enforce responsible AI standards.
GenAI Solution Engineering
- Work on RAG pipelines, document intelligence, OCR driven extraction, and knowledge grounded AI workflows.
- Integrate prompts into orchestration layers, APIs, and scalable production pipelines.
- Support deployment of cloud based AI services, preferably on Azure.
- Utilize leading LLM platforms such as OpenAI, Gemini, and similar enterprise models.
Cross Functional Collaboration
- Translate business workflows into effective AI conversations and user journeys.
- Partner with product owners, UX designers, and domain experts to enhance AI driven experiences.
- Contribute to architecture, tooling, and model selection decisions.
- Support enterprise pilots, rollout, and continuous optimization.
Leadership and Mentorship
- Act as subject matter expert in prompt engineering and Generative AI quality practices.
- Mentor junior engineers and define standards, review methods, and experimentation frameworks.
- Drive rapid learning cycles and innovation across AI teams.
Required Skills and Experience
Core Technical Skills
- 5+ years of experience in AI, NLP, or Generative AI related roles.
- Strong hands on expertise in prompt engineering, RAG, and LLM evaluation.
- Proficiency in Python and AI workflow orchestration.
- Experience working with cloud environments, preferably AWS.
- Hands on use of enterprise LLM platforms such as OpenAI or Gemini.
GenAI, Data, and Safety Capabilities
- Experience with OCR, document intelligence, embeddings, and vector databases.
- Understanding of hallucination control, response validation, and AI safety mechanisms.
- Ability to design regression testing and evaluation frameworks for prompts.
Domain and Product Mindset
- Ability to convert complex financial or enterprise workflows into AI driven solutions.
- Strong analytical thinking, experimentation mindset, and problem solving ability.
- Experience in financial services, wealth management, or enterprise SaaS is preferred.
Education
Bachelor’s degree or higher in Engineering, Computer Science, AI, or related discipline with 15 years of full time education.
Why Join Cognicor
- Build enterprise AI copilots for global financial institutions.
- Work on real world Generative AI deployments with measurable impact.
- Collaborate with strong AI, product, and domain teams in a fast growing environment.
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