Role at a Glance
Senior hybrid Sales Engineer role at Actian in Round Rock, TX. You are the company's vector database subject-matter expert: running enterprise proof-of-concepts, architecting Milvus and Qdrant solutions, and coaching the broader SE team globally. Requires 5+ years of pre-sales experience and production-level hands-on time with vector databases. Salary not listed by employer.
What This Role Is Actually About
Actian is expanding its Sales Engineering function with a specialist who can own the vector database conversation at the enterprise level. Unlike a generalist SE position, the mandate here is narrow and deep: become the definitive internal authority on AI data infrastructure, drive proof-of-concepts end-to-end using Milvus and Qdrant, and connect customers' AI/ML ambitions to Actian's multi-model platform. There is also a meaningful internal dimension — mentoring Sales Engineers across global regions and lifting the organization's collective knowledge of vector AI solutions.
About Actian
Actian builds data infrastructure for organizations where data failure is not an option. Their platform spans the full data lifecycle — integration, management, warehousing, and analytics — and it runs inside mission-critical systems at enterprises including Bloomberg, Citibank, Intuit, and Lufthansa. The platform's current differentiator is a vector-first capability embedded within a multi-model engine, so customers can run relational, analytical, and vector workloads together rather than assembling a stack of specialized point tools. Twenty-four Fortune 100 companies rely on Actian technology, giving the Sales Engineering team a credible reference base in competitive deals.
What You Will Own Day-to-Day
- Partner with Account Executives to identify, qualify, and close enterprise AI and data platform opportunities
- Lead technical qualification calls, architecture workshops, and requirements-scoping sessions throughout the pre-sales cycle
- Design and execute proof-of-concept projects showcasing Actian's vector database capabilities in competitive, enterprise-scale environments
- Build and deliver polished demonstrations and presentations tailored for both hands-on engineering teams and C-suite audiences
- Maintain deep, current competitive intelligence on vector database vendors and the broader analytics ecosystem
- Guide customers through technical challenges specific to their AI/ML stack and data architecture
- Route structured product feedback to Engineering, Product Management, and Marketing to inform the roadmap
- Mentor Sales Engineers across global regions, raising team-wide fluency in vector AI architecture and emerging patterns
- Cultivate long-term relationships with prospects and customers to build a reliable, repeatable pipeline
Must-Have Qualifications
- 5+ years in a customer-facing pre-sales or post-sales technical role
- Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or a related field — or demonstrably equivalent hands-on experience
- MUST HAVE: Production hands-on experience with Milvus and/or Qdrant vector databases
- Demonstrated expertise designing and implementing RAG (Retrieval Augmented Generation) architectures with LangChain integration
- Deep working knowledge of the vector AI landscape: embedding models, vector search algorithms, and enterprise AI/ML infrastructure patterns
- Extensive SQL proficiency and hands-on familiarity with large-scale analytics database systems such as Oracle, SQL Server, Snowflake, Teradata, and Netezza
- Proven record of closing data or analytics software deals at the enterprise level, including navigating complex multi-stakeholder buying cycles
- Experience with at least one major cloud IaaS platform: AWS, Microsoft Azure, or Google Cloud
- Ability to present and debate complex technical architectures fluently — whether at a whiteboard or in a formal demo — for both practitioner and executive audiences
Nice-to-Have Skills
- Hands-on experience with BI and data exploration tools such as Tableau, PowerBI, or Looker
- Background architecting solutions that blend vector, relational, and analytical workloads within a single multi-model database environment
- Familiarity with additional large-scale relational platforms beyond the core list (e.g., Informix, Netezza, IBM DB2)
- Experience designing or building AI/ML data pipelines that feed downstream vector search and retrieval use cases
Skills Map: Required vs. Nice-to-Have
The non-negotiable technical foundation is production experience with Milvus and/or Qdrant — this is an explicit hard requirement, not a soft preference. Layer on: RAG pipeline design, LangChain integration, and solid understanding of embedding model selection and vector indexing strategies. Relational and analytics database depth (Snowflake, Oracle, Teradata) is a supporting must-have rather than mere background context — enterprise deals consistently require positioning vector capabilities alongside existing data warehouse investments. BI tool familiarity (Tableau, PowerBI, Looker) and broad cloud IaaS knowledge are nice-to-haves that accelerate onboarding but are not disqualifying gaps.
Salary & Compensation
Actian has not published a salary range for this position. No benefits details are specified in the employer's listing either. Candidates should conduct independent market research on current compensation for senior-level Sales Engineers in the Texas data and AI infrastructure sector. We recommend surfacing your expectations directly with the recruiter in your first screening call — this is a specialized role requiring rare production experience with Milvus or Qdrant, and both parties benefit from aligning on range early rather than late.
Location & Work Model
This position is based in Round Rock, Texas, and operates on a hybrid schedule combining in-office and remote workdays. The posting does not specify the required on-site frequency or designated office days. Visa sponsorship availability and relocation assistance are not mentioned in the employer's listing — candidates with relocation or work-authorization requirements should confirm these details directly during the recruiting process.