The Role
Lead technical vision and delivery of AI/ML and Generative AI solutions (LLMs, computer vision, forecasting). Mentor engineers, design architectures, build RAG pipelines, manage ML lifecycle, deploy and monitor models on AWS, and collaborate with stakeholders to translate business problems into scalable AI systems.
Summary Generated by Built In
Job Summary:
We are looking for a highly skilled Lead AI/ML Engineer with 6+ years of hands-on experience in designing, deploying, and scaling AI/ML and Generative AI solutions. The ideal candidate will lead technical efforts across a wide spectrum of AI technologies—including large language models (LLMs), computer vision, machine learning, and data science—to solve high-impact business problems. This is a technical leadership role that involves mentoring team members, shaping architecture decisions, and driving end-to-end AI solution delivery across cloud-based environments.
Key Responsibilities:
Leadership & Strategy- Drive the technical vision and roadmap for AI/ML and Generative AI initiatives.
- Lead and mentor a team of AI/ML engineers and data scientists, conducting regular code reviews and guiding solution architecture.
- Collaborate with cross-functional stakeholders to translate business problems into scalable AI/ML solutions.
- Own the AI/ML lifecycle—from prototyping and experimentation to production deployment and monitoring.
- Architect and lead the development of scalable Generative AI solutions using AWS Cloud and modern frameworks.
- Deep experience in working with large language models (LLMs) including fine-tuning, evaluation, and deployment.
- Expertise in prompt engineering, agentic workflows, and custom LLM development.
- Proficient with Langchain, Langgraph, Langfuse, Crew AI, and other GenAI frameworks.
- Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise applications.
- Solve complex machine learning problems using supervised, unsupervised, and deep learning methods.
- Lead the implementation of ML pipelines including automated data preprocessing, training, validation, and monitoring.
- Manage ML lifecycle using AWS SageMaker, including model versioning, drift detection, and retraining strategies.
- Apply advanced analytics, time series forecasting, and predictive modeling techniques.
- Design and deploy advanced computer vision models for tasks such as classification, object detection, segmentation, and image captioning.
Skills & Qualifications:
- 6+ years of experience in AI/ML, with at least 3 years in Generative AI and LLMs.
- Strong proficiency in Python and ML libraries such as Scikit-learn, XGBoost, LightGBM, CatBoost.
- Deep understanding of LLMs including OpenAI (GPT-4, GPT-4o), Claude, Gemini, LLaMa, DeepSeek, etc.
- Proficiency with GenAI tooling: Langchain, Langfuse, Crew AI, LLAMA Index, Langgraph, etc.
- Experience working with vector databases (Pinecone, FAISS, OpenSearch, Chroma) and indexing strategies.
- Hands-on with deep learning frameworks such as PyTorch and TensorFlow.
- Strong experience with AWS services: SageMaker, Bedrock, DynamoDB, S3, Lambda, etc.
- Proficiency in REST API development using FastAPI, Uvicorn, Flask, Docker, and related tools.
- Strong database knowledge—both SQL (PostgreSQL) and NoSQL (DynamoDB).
- Familiarity with caching systems like Redis and Memcached.
- Strong communication skills and ability to lead discussions with both technical and non-technical stakeholders.
Preferred:
- Experience in leading enterprise-scale AI/ML deployments.
- Contributions to open-source GenAI/ML projects.
- Certifications in AWS AI/ML or equivalent.
Skills Required
- 6+ years of experience in AI/ML with at least 3 years in Generative AI and LLMs
- Strong proficiency in Python
- Experience with ML libraries: Scikit-learn, XGBoost, LightGBM, CatBoost
- Deep understanding of LLMs (OpenAI GPT-4/GPT-4o, Claude, Gemini, LLaMa, DeepSeek) and LLM evaluation/fine-tuning
- Proficiency with GenAI tooling: Langchain, Langfuse, Crew AI, LLAMA Index, Langgraph
- Experience with vector databases and indexing strategies (Pinecone, FAISS, OpenSearch, Chroma)
- Hands-on experience with PyTorch and TensorFlow
- Strong experience with AWS services (SageMaker, Bedrock, DynamoDB, S3, Lambda)
- Proficiency building REST APIs and deployments using FastAPI, Uvicorn, Flask, and Docker
- Strong database knowledge (PostgreSQL and NoSQL such as DynamoDB)
- Familiarity with caching systems like Redis and Memcached
- Strong communication and leadership skills to mentor teams and collaborate with stakeholders
- Experience in leading enterprise-scale AI/ML deployments
- Contributions to open-source GenAI/ML projects
- Certifications in AWS AI/ML or equivalent
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The Company
What We Do
Armakuni is a cloud-native technology consultancy and AWS Premier Partner dedicated to accelerating digital transformation for organizations worldwide. They specialize in driving digital transformation and accelerating software delivery by helping organizations use cloud-native technologies to drive growth, increase efficiency, and enhance customer value. Their expertise spans cloud advisory, deployment, integration, data engineering, and migration, positioning them as a key engineering partner for the AI era.
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