Hiring Gen AI Developer

Generative AI Developer / Engineer / Analyst

Experience

• 23 years of hands-on experience working with Generative AI technologies

(Recognizing the relative newness of GenAI as a field)

• 2–3 years of experience in data analysis, business analysis, or analytics-heavy roles

Role Summary

We are seeking a Generative AI Developer/Analyst who combines strong data and analytical thinking with the

ability to effectively design, test, and optimize LLM-powered solutions. While traditional programming skills are

important, this role places a strong emphasis on data understanding, prompt engineering, and written

communication, as English is effectively the “programming language” of GenAI systems.

The ideal candidate is a technologist first, comfortable coding in any modern language, and equally comfortable

working with data, requirements, and stakeholders.

Key Responsibilities

Generative AI Development

• Design, build, and optimize applications using Large Language Models (LLMs) such as LLama, GPT, Claude,

Gemini, or similar

• Develop and refine prompt engineering strategies to improve accuracy, reliability, and consistency of

GenAI outputs

• Implement prompt versioning, evaluation, and experimentation frameworks

• Apply techniques such as few-shot learning, chain-of-thought prompting, RAG (Retrieval-Augmented

Generation), and tool/function calling

Data & Analysis

• Analyze structured and unstructured data to determine suitability for GenAI use cases

• Work closely with business stakeholders to translate requirements into LLM-ready inputs and workflows

• Perform data profiling, cleansing, and transformation to support GenAI pipelines

• Evaluate model outputs using qualitative and quantitative metrics

Engineering & Integration

• Implement GenAI solutions using any modern programming language (e.g., Python, Java, JavaScript, Go,

etc.)

• Integrate LLMs with APIs, databases, vector stores, and enterprise systems

• Build scalable and secure GenAI services following engineering best practices

• Collaborate with DevOps and cloud teams for deployment and monitoring

Communication & Documentation

• Produce clear, well-structured written documentation (prompts, design docs, evaluation criteria)

• Communicate complex AI behavior and limitations to non-technical stakeholders

• Maintain prompt libraries, usage guidelines, and best practices

Required Skills & Qualifications

Core Requirements

• 2–3 years experience working with Generative AI / LLM-based systems

• 1–3 years hands-on experience with prompt engineering

• Strong written English skills with the ability to craft precise, unambiguous instructions

• Strong data analysis or business analysis background (2–3 years)

• Ability to code in at least one programming language (language-agnostic mindset)

• Solid understanding of:

• LLM behavior, strengths, and limitations
• Tokenization, context windows, and cost/performance trade-offs
• Hallucinations, bias, and output validation techniques

Technical Knowledge

• Experience with:

• OpenAI / Azure OpenAI / Anthropic / Google GenAI APIs
• Vector databases (e.g., Pinecone, FAISS, Weaviate, OpenSearch)
• RAG architectures

• Familiarity with:

• APIs and microservices
• SQL and/or NoSQL databases
• Cloud platforms (AWS, Azure, or GCP)

Preferred / Nice-to-Have Skills

• Experience building enterprise GenAI solutions

• Knowledge of evaluation frameworks for LLM outputs

• Experience with document processing, summarization, or contract analysis

• Understanding of data privacy, security, and compliance in AI systems

• Exposure to MLOps / LLMOps concepts

Mindset & Traits

• Strong analytical and problem-solving skills

• Curious, experimental, and comfortable with ambiguity

• Ability to think in language, logic, and data simultaneously

• Business-oriented mindset with attention to real-world impact

Why This Role Is Different

• GenAI development is not only about coding

• English is a core development skill

• Success depends on data understanding, prompt design, and analysis, as much as software engineering