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AI Engineer – AWS & Amazon Bedrock
LinkedIn Recruiter Post
Experienced AI Engineer needed to design and deploy enterprise - grade Generative AI solutions using AWS cloud - native technologies, LLMs, and Amazon Bedrock.
About the role
- Senior AI/ML Developer at Tecsys leveraging AI/ML technologies for supply chain innovations. Collaborating with development teams to enhance operational efficiency with advanced data solutions.
Responsibilities
- You will be the AI expert on the team and work closely with development teams to drive the creation of new features and provide actionable business insights to our clients and end users.
- You will identify, coordinate, and develop data science solutions to build predictive and prescriptive models, and design AI/ML/agent solutions using data pipelines to solve supply chain problems.
- You will also contribute to the design and development of production-quality AI systems, including LLM-based features, retrieval-augmented generation (RAG) pipelines, and multi-step agent workflows.
- You will help transform experimental AI capabilities into reliable, scalable, and measurable product features.
- Although end-to-end solution deployment and lifecycle management are not your primary responsibility, you will contribute to the process, including developing tools to evaluate model effectiveness.
Requirements
- You hold a Master’s degree in Computer Science or a related discipline (e.g., Engineering, Physics, Applied Mathematics, Statistics).
- You have proven experience converting business problems into mathematical representations to drive AI/ML algorithms.
- You are an expert in Python with demonstrated experience using supervised, unsupervised, and semi-supervised machine learning solutions.
- You are proficient in statistical models, optimization and mathematical programming (OR), metaheuristics, and deep reinforcement learning, and know how to apply them to create business value.
- You have hands-on experience designing and implementing modern AI systems, including LLM-based applications, prompt engineering, and retrieval-based systems.
- You can evaluate and monitor AI systems, including defining accuracy, validation, and performance metrics over time.
- You are well-versed in the data science ecosystem (NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow, etc.).
- You have solid experience with cloud-based AI/ML solutions (e.g., AWS, Azure, GCP).
- You can communicate technical concepts clearly to multidisciplinary teams, including management and non-technical stakeholders.
- You have at least 5–7 years of experience developing AI/ML-based solutions in Python.
- What could give you an advantage?
- Experience designing and deploying production AI systems (e.g., APIs, microservices, or agent-based systems)
- Familiarity with LLM orchestration frameworks (e.g., LangChain, LangGraph) and vector databases
- Experience with MLOps practices, including model and version management, evaluation pipelines, and monitoring
- Strong understanding of trade-offs inherent to AI systems (accuracy vs. latency vs. cost)
- Strong supply chain management experience
- Bilingual
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