Jobs at Yahara Software

Own technical delivery for software projects serving scientific and life sciences organizations. Lead architecture, development, deployment, testing, and release activities; translate requirements into actionable work; mentor engineers; communicate technical decisions and risks to clients; support pre-sales estimates; and incorporate AI-assisted development tools into engineering workflows. The role involves cloud application development on AWS or Azure and technical leadership without direct people management.

Leads client-facing applied AI/ML projects, setting technical direction and delivering LLM, RAG, agent, model adaptation, evaluation, and safety solutions. Mentors engineers, owns delivery quality, communicates tradeoffs to clients, supports presales, and documents architecture decisions. Requires six-plus years of software engineering experience and hands-on experience shipping LLM applications.

Leads software, requirements, and QA engineering teams through career development, performance management, hiring, onboarding, staffing, and conflict resolution. Partners with technical leads and project managers to support project health and delivery, while contributing hands-on technical work as needed. Uses AI tools to improve management workflows and maintains strong engineering, testing, architecture, and quality standards.

Build and maintain full-stack software for life sciences organizations, laboratories, CROs, and scientific instrument developers. Responsibilities include developing web applications and services, working across databases and user interfaces, testing and deploying applications to AWS or Azure, participating in Agile ceremonies, reviewing code, using AI-assisted development tools, and owning features from design through delivery. The role also involves client collaboration, continuous learning, and potentially mentoring engineers or leading small projects.

The Business Analyst serves as a Requirements Engineer, gathering and analyzing stakeholder needs, documenting software requirements, creating user stories and process diagrams, and supporting Agile development teams. Responsibilities include prioritizing features, tracking requirements, facilitating Scrum ceremonies, coordinating testing feedback, prioritizing defects, and collaborating with clients, technical leads, and project teams. The role also supports requirements practice improvements and applies AI tools to research and documentation while validating AI-generated outputs.

Lead machine learning engineering for client projects, designing, training, evaluating, deploying, monitoring, and retraining models. Set technical direction, mentor engineers, define evaluation standards, shape data into features, collaborate with DevOps, document architecture decisions, communicate tradeoffs to clients, and support pre-sales solution development.