GenAI Developer

Requirements

• Bachelor's or Master's degree in Computer Science, Data Science, AI, or related disciplines.
• 7+ years of experience in AI/ML development with specific focus on LLMs and Generative AI.
• Proven leadership in deploying large-scale AI solutions in enterprise environments.
• Relevant certifications in cloud platforms, AI, or ML frameworks are a plus.
• Strong comm

Benefits

Additional Information

Job Summary Synechron is seeking an experienced Lead GenAI Developer to spearhead the design, development, and deployment of innovative Generative AI solutions. This role involves leading the implementation of large language models (LLMs), developing intelligent workflows, and integrating AI capabilities into business platforms. The ideal candidate will possess deep technical expertise, demonstrate leadership in emerging AI technologies, and collaborate effectively with cross-disciplinary teams to drive organizational innovation and competitive advantage. Software Requirements Required: Strong hands-on experience with Python for developing AI/ML applications and leveraging frameworks such as TensorFlow or PyTorch . Practical experience with Large Language Models (LLMs) , Prompt Engineering, and RAG (Retrieval-Augmented Generation) pipelines. Familiarity with AWS Bedrock , Lambda , API Gateway , and SageMaker for building scalable LLM-based solutions. Knowledge of tools like LangChain , Agent Core , and other frameworks for AI workflows and agent orchestration. Experience integrating AI models with enterprise systems, APIs, and vector databases (FAISS, Pinecone). Proficiency in version control (Git) and containerization (Docker). Preferred: Experience with cloud deployment platforms such as Azure or GCP . Exposure to other AI frameworks such as Hugging Face Transformers or DeepResearch stacks. Basic familiarity with Terraform or Helm for infrastructure automation. Skills in scripting languages such as Shell or Bash . Overall Responsibilities Lead the end-to-end development and deployment of Generative AI and LLM-based solutions aligned with business needs. Provide technical leadership, mentorship, and guidance to engineering teams working on AI projects. Evaluate, recommend, and implement new AI tools, frameworks, and platform innovations to enhance capabilities and efficiencies. Collaborate with product owners, architecture teams, and business stakeholders to translate requirements into technical solutions. Design and optimize workflows supporting prompt engineering, model tuning, and data ingestion processes. Ensure AI models and systems are scalable, robust, and aligned with organizational standards and best practices. Stay current with AI research, emerging trends, and industry standards, advocating for innovation within the organization. Expected outcomes: Deliver cutting-edge, scalable, and reliable AI solutions that support business transformation initiatives and competitive differentiation. Technical Skills (By Category) Programming Languages: Essential: Python (advanced, especially for AI/ML development), optionally JavaScript or TypeScript for API integrations. Preferred: Java, R, or other languages used in AI/ML deployment. Frameworks & Libraries: Essential: TensorFlow, PyTorch, Hugging Face Transformers, LangChain, and custom API integrations. Preferred: DeepResearch, GPT frameworks, or additional NLP toolkits. Cloud Technologies: Essential: AWS Bedrock, Lambda, API Gateway, SageMaker, and cloud deployment best practices. Preferred: Azure, GCP, or multi-cloud deployment experience. Data & Storage: Experience with vector databases such as FAISS, Pinecone, or Weaviate. DevOps & Automation Tools: Essential: Docker, Git, CI/CD pipelines (e.g., Jenkins, GitHub Actions). Preferred: Terraform, Helm, Kubernetes. Security & Data Privacy: Knowledge of model versioning, data encryption, and compliance standards associated with AI solutions. Experience Requirements Minimum of 7+ years of experience in AI/ML development, especially with LLMs and prompt engineering. Demonstrated success leading AI/ML projects from conception to deployment in production environments. Proven experience mentoring and guiding technical teams on AI best practices. Industry experience in finance, healthcare, or enterprise tech sectors is preferred; relevant research or academic projects also acceptable. Day-to-Day Activities Lead the design, development, and deployment of generative AI models and workflows. Guide and mentor junior engineers and data scientists on AI/ML best practices. Collaborate with stakeholders to translate business needs into scalable AI solutions. Evaluate new AI tools, frameworks, and datasets to expand capabilities. Optimize models, workflows, and infrastructure for performance and scalability. Monitor, troubleshoot, and update deployed models to maintain performance and relevance. Document architecture, workflows, and AI pipeline processes; present findings to technical and non-technical audiences.

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