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Senior AI Engineer – Hakkoda (now part of IBM) We are looking for a Senior AI Engineer with a strong track record of developing and deploying AI solutions, especially large language models (LLMs), agents, and retrieval‑augmented generation (RAG) pipelines. This role involves close collaboration with clients to architect, build, and deliver real‑world solutions using Snowflake, AWS, and Google Cloud. The ideal candidate balances technical depth with a pragmatic, delivery‑oriented mindset and excellent communication skills.
Key Responsibilities
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.
Preferred Education Master’s Degree
Required Technical And Professional Expertise
Education: Bachelor’s degree in Computer Science, Data Science, AI, or a related field.
Experience: 5–7 years in AI engineering, machine learning, or related fields; demonstrated experience in a professional services or consulting environment with client‑facing responsibilities.
Must‑Have Skills and Experience:
Proven experience 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 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.
Excellent communication skills for translating complex technical concepts to diverse audiences.
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.
Preferred Technical And Professional Experience
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.
Extensive experience with industry‑specific AI applications (healthcare, finance, supply chain, or retail/CPG).
Advanced proficiency in natural language processing (NLP) and computer vision technologies.
Master’s or Ph.D. preferred.
This role can be performed from anywhere in the US.
Referrals increase your chances of interviewing at IBM by 2×.
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Senior AI Engineer – Hakkoda (now part of IBM) We are looking for a Senior AI Engineer with a strong track record of developing and deploying AI solutions, especially large language models (LLMs), agents, and retrieval‑augmented generation (RAG) pipelines. This role involves close collaboration with clients to architect, build, and deliver real‑world solutions using Snowflake, AWS, and Google Cloud. The ideal candidate balances technical depth with a pragmatic, delivery‑oriented mindset and excellent communication skills.
Key Responsibilities
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.
Preferred Education Master’s Degree
Required Technical And Professional Expertise
Education: Bachelor’s degree in Computer Science, Data Science, AI, or a related field.
Experience: 5–7 years in AI engineering, machine learning, or related fields; demonstrated experience in a professional services or consulting environment with client‑facing responsibilities.
Must‑Have Skills and Experience:
Proven experience 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 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.
Excellent communication skills for translating complex technical concepts to diverse audiences.
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.
Preferred Technical And Professional Experience
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.
Extensive experience with industry‑specific AI applications (healthcare, finance, supply chain, or retail/CPG).
Advanced proficiency in natural language processing (NLP) and computer vision technologies.
Master’s or Ph.D. preferred.
This role can be performed from anywhere in the US.
Referrals increase your chances of interviewing at IBM by 2×.
#J-18808-Ljbffr