{"id":1289531,"url":"https://alion.io/job/mammoth-biosciences-senior-software-engineer-i-research-informatics","title":"Senior Software Engineer I, Research Informatics","company":{"id":1900077,"name":"Mammoth Biosciences","domain":"mammoth.bio","url":"https://alion.io/company/mammoth-bio","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":null},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Brisbane, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":142000,"max":178000,"currency":"USD","period":"year","gross":null,"usd_annual":178000},"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon EC2","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"ETL/ELT","optional":true},{"name":"Prefect","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-08-10T22:47:22Z","employer_posted_date":"2026-08-10","last_verified_at":"2026-10-20T21:59:32Z","board_verified":true,"closed_at":null,"days_open":70,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":70},"description":"OPPORTUNITY\nMammoth Biosciences is seeking a Senior Software Engineer I, Research Informatics, to join our Computational team. This is an impactful group of bioinformaticians and software engineers that supports Mammoth's therapeutic CRISPR gene-editing programs from discovery through IND-enabling studies. As part of the Computational team, you’ll help build and run the analysis pipelines, model and manage the data those programs generate, and develop the internal tools scientists use to design experiments and interpret results.\nAn ideal candidate will work at the intersection of software engineering and biology. You’ll be responsible for managing and improving the systems the research organization depends on every day: the data warehouse and models that connect assay results to decisions, the internal web applications scientists use to launch analyses and access their data, and the cloud infrastructure everything runs on.\nKEY RESPONSIBILITIES\nDesign and own relational data models and pipelines that drive scientific decisions, working in the context of existing production systems including Benchling\nDefine and refine how data is ingested, modeled, and made queryable\nCollaborate with wet-lab scientists to build right-sized internal analysis tools\nDesign and improve the web applications scientists use to launch analyses and access data\nMaintain the cloud infrastructure and automation tooling the research org runs on\nWork directly with Computational team members and biologists to understand scientific needs, then troubleshoot and improve the relevant pipelines and systems\nEnable responsible and reproducible use of AI across the company\nDocument systems and decisions to improve reproducibility and engineering standards\nREQUIRED QUALIFICATIONS\nBachelor's, Master's, or PhD degree (or equivalent combination of education and experience) in computer sciences or biological field \n7+ years of professional software engineering experience (5 years with Master's or 3 years with PhD) in the life sciences or related industry\nStrong proficiency in Python\nHands-on experience with AWS services (e.g. S3, Batch, RDS, EC2, Lambda) and containerized deployment (Docker)\nExperience with web development tools (ReactJS, HTML, CSS)\nExperience in SQL, designing relational data models and working with production databases\nExperience with AI coding tools\nExperience working with scientists, preferably in genomics (with NGS data) or related field\nProficiency with git-based collaborative development, code review, automated testing, and CI/CD\nAbility to work onsite 2x/per week at our Brisbane HQ\nPREFERRED QUALIFICATIONS\nExperience with workflow orchestration systems (Prefect, Nextflow, CWL, Airflow)\nExperience with LIMS/ELN data modeling, preferably Benchling\nExperience building and operating data pipelines or ETL systems, and comfort owning them end to end\nExperience with analytics engineering tooling (DBT) and data warehouse design\nTrack record of building tools used by scientists or other non-engineer users, and of translating ambiguous requirements into working software\nDemonstrated ability to work independently in a small team where priorities shift and everyone wears many hats\nBackground -- or real interest -- in the underlying biology, and the communication skills to work directly with bench scientists\nInfrastructure-as-code experience (Terraform)\nThoughtful, productive use of AI coding tools, and a considered point of view on where they help and where they do not\nBENEFITS\nCompany-paid health/vision/dental benefits\nUnlimited vacation and generous sick time\nCompany-sponsored meals and snacks\nWellness, caregiver and ergonomics benefits\n401(k) with company matching","description_format":"text","description_chars":3702,"description_truncated":false,"requirements":{"experience_years_min":7,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Synthetic Biology","Rare Disease Therapeutics"],"lifecycle":[{"event":"open","at":"2026-09-26T07:34:21Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 4","filings_12m":4,"filings_prev_12m":4,"green_card_filings_12m":0,"median_offered_wage_usd":142500,"route":null,"cap_exempt":false,"checked_at":"2026-10-15T11:24:14+00:00","sources":["US Department of Labor: LCA disclosure data 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