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A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.

In this role, you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology.

What you'll do:

• Solution Architecture: Lead the design and development of LLM-based solutions including RAG pipelines, agent workflows, and generative AI applications.

• Multi-Platform Implementation: Develop and deploy AI solutions across Snowflake, AWS, Google Cloud, Databricks, and other enterprise environments.

• Client-Facing Delivery: Work directly with clients to understand business needs, propose architectures, and implement solutions that deliver measurable value.

• Model Development & Optimization: Fine-tune models, build embedding workflows, implement vector search, and monitor performance in production environments.

• Workflow Automation & Integration: Architect AI systems that integrate with cloud-based data pipelines and enterprise tools, ensuring reliability and scalability.

• Mentorship & Collaboration: Provide technical leadership, mentor junior engineers, and contribute to the growth of Hakkoda’s AI practice.

• Innovation & Research: Stay informed on emerging AI technologies and bring innovative capabilities into production use.

What you'll bring:

• Education: Bachelor’s degree in Computer Science, Data Science, AI, or a related field (Master’s or Ph.D. preferred).

• Experience:

• Minimum of 5-7 years of experience in AI engineering, machine learning, or related fields.

• Demonstrated experience working in a professional services or consulting environment with client-facing responsibilities.

• Must-Have Skills and Experience

• Proven experience developing and deploying LLM-powered applications into production

• Strong background in RAG architecture, vector search, and embedding pipelines

• Familiarity with agent frameworks such as LangChain, LlamaIndex, or CrewAI

• Expertise in Python, with sound software engineering practices

• Experience working with Snowflake, including Cortex and UDFs for AI integration

• Hands-on experience deploying AI solutions on multiple cloud platforms (especially AWS and GCP)

• Strong client-facing skills, with the ability to lead technical discussions and present to stakeholders

• Demonstrated ability to scope, build, and deliver full AI solutions—not just prototypes

• Nice-to-Have Skills

• Experience with LLMOps tools (PromptLayer, LangSmith, Weights & Biases, etc.)

• Understanding of AI cost optimization and production reliability concerns

• Prior experience with consulting or professional services engagements

• Experience building AI solutions with synthetic or simulated data

• Contributions to open-source AI projects or active involvement in AI communities

Soft Skills:

• Excellent communication skills, with the ability to translate complex technical concepts for diverse audiences, including clients.

• Strong leadership skills, with a track record of successfully managing projects and mentoring junior team members.

• Problem-solving expertise with a creative approach to overcoming client challenges and delivering results under tight timelines.

• Preferred Qualifications:

  • Extensive experience with industry-specific AI applications, such as healthcare, finance, supply chain, or retail/CPG.

  • Advanced proficiency in natural language processing (NLP) and computer vision technologies.

  • Previous experience leading teams or projects in an Agile or Scrum environment.

• Cloud Integration Knowledge: Exposure to integrating cloud computing concepts and technologies with Snowflake platforms, enhancing data and AI use case implementation. • Advanced Data Engineering: Experience working with data engineering principles and practices to deliver high-quality solutions on Snowflake platforms, leveraging expertise in Snowflake and cloud computing. • Technical Solution Optimization: Experience applying technical expertise to optimize solutions on Snowflake platforms, ensuring seamless integration and optimal performance for data and AI use cases.